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Bob Nishikawa

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Wu, C.C., D'Ardenne, N.M., Nishikawa, R.M., & Wolfe, J.M. (2020). Gist processing in digital breast tomosynthesis. J Med Imaging (Bellingham), 7(2), 022403.SPIE-Intl Soc Optical Eng. doi: 10.1117/1.JMI.7.2.022403.

de Cea, M.V.S., Nishikawa, R.M., & Yang, Y. (2018). Locally adaptive decision in detection of clustered microcalcifications in mammograms. PHYSICS IN MEDICINE AND BIOLOGY, 63(4), 045014.IOP Publishing. doi: 10.1088/1361-6560/aaaa4c.

Lee, J., & Nishikawa, R.M. (2018). Automated mammographic breast density estimation using a fully convolutional network. MEDICAL PHYSICS, 45(3), 1178-1190.Wiley. doi: 10.1002/mp.12763.

Lee, J., Nishikawa, R.M., Reiser, I., & Boone, J.M. (2018). Neutrosophic segmentation of breast lesions for dedicated breast computed tomography. J Med Imaging (Bellingham), 5(1), 014505.SPIE-Intl Soc Optical Eng. doi: 10.1117/1.JMI.5.1.014505.

Nishikawa, R.M., & Bae, K.T. (2018). Importance of Better Human-Computer Interaction in the Era of Deep Learning: Mammography Computer-Aided Diagnosis as a Use Case. JOURNAL OF THE AMERICAN COLLEGE OF RADIOLOGY, 15(1), 49-52.Elsevier BV. doi: 10.1016/j.jacr.2017.08.027.

Chakraborty, D.P., Nishikawa, R.M., & Orton, C.G. (2017). Due to potential concerns of bias and conflicts of interest, regulatory bodies should not do evaluation methodology research related to their regulatory missions. MEDICAL PHYSICS, 44(9), 4403-4406.Wiley. doi: 10.1002/mp.12373.

de Cea, M.V.S., Nishikawa, R.M., & Yang, Y. (2017). Estimating the Accuracy Level Among Individual Detections in Clustered Microcalcifications. IEEE TRANSACTIONS ON MEDICAL IMAGING, 36(5), 1162-1171.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TMI.2017.2654799.

Lee, J., Nishikawa, R.M., Reiser, I., & Boone, J.M. (2017). Optimal reconstruction and quantitative image features for computer-aided diagnosis tools for breast CT. MEDICAL PHYSICS, 44(5), 1846-1856.Wiley. doi: 10.1002/mp.12214.

Lee, J., Nishikawa, R.M., Reiser, I., Zuley, M.L., & Boone, J.M. (2017). Lack of agreement between radiologists: implications for image-based model observers. J Med Imaging (Bellingham), 4(2), 025502.SPIE-Intl Soc Optical Eng. doi: 10.1117/1.JMI.4.2.025502.

Wang, J., Nishikawa, R.M., & Yang, Y. (2017). Quantitative comparison of clustered microcalcifications in for-presentation and for-processing mammograms in full-field digital mammography. MEDICAL PHYSICS, 44(7), 3726-3738.Wiley. doi: 10.1002/mp.12316.

Wang, J., Nishikawa, R.M., & Yang, Y. (2017). Global detection approach for clustered microcalcifications in mammograms using a deep learning network. J Med Imaging (Bellingham), 4(2), 024501.SPIE-Intl Soc Optical Eng. doi: 10.1117/1.JMI.4.2.024501.

Reiser, I., Lau, B., & Nishikawa, R.M. (2016). Tomosynthesis system modeling. In Tomosynthesis Imaging. (pp. 81-97).

Wang, J., Nishikawa, R.M., & Yang, Y. (2016). Improving the accuracy in detection of clustered microcalcifications with a context-sensitive classification model. MEDICAL PHYSICS, 43(1), 159-170.Wiley. doi: 10.1118/1.4938059.

Wu, S., Berg, W.A., Zuley, M.L., Kurland, B.F., Jankowitz, R.C., Nishikawa, R., Gur, D., & Sumkin, J.H. (2016). Breast MRI contrast enhancement kinetics of normal parenchyma correlate with presence of breast cancer. BREAST CANCER RESEARCH, 18(1), 76.Springer Science and Business Media LLC. doi: 10.1186/s13058-016-0734-0.

de Sisternes, L., Brankov, J.G., Zysk, A.M., Schmidt, R.A., Nishikawa, R.M., & Wernick, M.N. (2015). A computational model to generate simulated three-dimensional breast masses. MEDICAL PHYSICS, 42(2), 1098-1118.Wiley. doi: 10.1118/1.4905232.

Gur, D., Nishikawa, R.M., & Sumkin, J.H. (2015). New Screening Technologies and Practices: A Different Approach to Estimation of Performance Improvement by Using Data from the Transition Period. RADIOLOGY, 275(1), 9-12.Radiological Society of North America (RSNA). doi: 10.1148/radiol.14141843.

Lee, J., Nishikawa, R.M., Reiser, I., Boone, J.M., & Lindfors, K.K. (2015). Local curvature analysis for classifying breast tumors: Preliminary analysis in dedicated breast CT. MEDICAL PHYSICS, 42(9), 5479-5489.Wiley. doi: 10.1118/1.4928479.

Tanaka, R., Takamori, M., Uchiyama, Y., Nishikawa, R.M., & Shiraishi, J. (2015). Using breast radiographers' reports as a second opinion for radiologists' readings of microcalcifications in digital mammography. BRITISH JOURNAL OF RADIOLOGY, 88(1047), 20140565.British Institute of Radiology. doi: 10.1259/bjr.20140565.

Nishikawa, R.M., & Gur, D. (2014). CADe for Early Detection of Breast Cancer - Current Status and Why We Need to Continue to Explore New Approaches. ACADEMIC RADIOLOGY, 21(10), 1320-1321.Elsevier BV. doi: 10.1016/j.acra.2014.05.018.

Wang, J., Jing, H., Wernick, M.N., Nishikawa, R.M., & Yang, Y. (2014). Analysis of perceived similarity between pairs of microcalcification clusters in mammograms. MEDICAL PHYSICS, 41(5), 051904.Wiley. doi: 10.1118/1.4870959.

Altman, M.B., Flynn, M.J., Nishikawa, R.M., Chetty, I.J., Barton, K.N., Movsas, B., Kim, J.H., & Brown, S.L. (2013). The potential of iodine for improving breast cancer diagnosis and treatment. MEDICAL HYPOTHESES, 80(1), 94-98.Elsevier BV. doi: 10.1016/j.mehy.2012.10.018.

Chen, X., Nishikawa, R.M., Chan, S.T., Lau, B.A., Zhang, L., & Mou, X. (2013). Algorithmic scatter correction in dual-energy digital mammography. MEDICAL PHYSICS, 40(11), 111919.Wiley. doi: 10.1118/1.4826173.

D'Orsi, C.J., Getty, D.J., Pickett, R.M., Sechopoulos, I., Newell, M.S., Gundry, K.R., Bates, S.R., Nishikawa, R.M., Sickles, E.A., Karellas, A., & D'Orsi, E.M. (2013). Stereoscopic Digital Mammography: Improved Specificity and Reduced Rate of Recall in a Prospective Clinical Trial. RADIOLOGY, 266(1), 81-88.Radiological Society of North America (RSNA). doi: 10.1148/radiol.12120382.

Nishikawa, R.M. (2013). Computer-aided Detection of Masses at Mammography: Interactive Decision Support Versus Prompts. Breast Diseases: A Year Book Quarterly, 24(3), 227-228.Elsevier BV. doi: 10.1016/j.breastdis.2013.07.023.

Nishikawa, R.M., & Pesce, L.L. (2013). Estimating Sensitivity and Specificity for Technology Assessment Based on Observer Studies. ACADEMIC RADIOLOGY, 20(7), 825-830.Elsevier BV. doi: 10.1016/j.acra.2013.03.008.

Reiser, I., Edwards, A., & Nishikawa, R.M. (2013). Validation of a power-law noise model for simulating small-scale breast tissue. PHYSICS IN MEDICINE AND BIOLOGY, 58(17), 6011-6027.IOP Publishing. doi: 10.1088/0031-9155/58/17/6011.

Cole, E.B., Zhang, Z., Marques, H.S., Nishikawa, R.M., Hendrick, R.E., Yaffe, M.J., Padungchaichote, W., Kuzmiak, C., Chayakulkheeree, J., Conant, E.F., Fajardo, L.L., Baum, J., Gatsonis, C., & Pisano, E. (2012). Assessing the Stand-Alone Sensitivity of Computer-Aided Detection With Cancer Cases From the Digital Mammographic Imaging Screening Trial. AMERICAN JOURNAL OF ROENTGENOLOGY, 199(3), W392-W401.American Roentgen Ray Society. doi: 10.2214/AJR.11.7255.

Jing, H., Yang, Y., & Nishikawa, R.M. (2012). Regularization in retrieval-driven classification of clustered microcalcifications for breast cancer. Int J Biomed Imaging, 2012, 463408.Hindawi Limited. doi: 10.1155/2012/463408.

Jing, H., Yang, Y., & Nishikawa, R.M. (2012). Retrieval boosted computer-aided diagnosis of clustered microcalcifications for breast cancer. MEDICAL PHYSICS, 39(2), 676-685.Wiley. doi: 10.1118/1.3675600.

Jing, H., Yang, Y., Wernick, M.N., Yarusso, L.M., & Nishikawa, R.M. (2012). A comparison study of image features between FFDM and film mammogram images. MEDICAL PHYSICS, 39(7), 4386-4394.Wiley. doi: 10.1118/1.4729740.

Lau, B.A., Reiser, I., Nishikawa, R.M., & Bakic, P.R. (2012). A statistically defined anthropomorphic software breast phantom. MEDICAL PHYSICS, 39(6), 3375-3385.Wiley. doi: 10.1118/1.4718576.

Nishikawa, R.M., Fenton, J.J., & Orton, C.G. (2012). Computer-aided detection should be used routinely to assist screening mammogram interpretation. MEDICAL PHYSICS, 39(9), 5305-5307.Wiley. doi: 10.1118/1.3694117.

Nishikawa, R.M., Giger, M.L., Jiang, Y., & Metz, C.E. (2012). Re: Effectiveness of Computer-Aided Detection in Community Mammography Practice. JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE, 104(1), 77.Oxford University Press (OUP). doi: 10.1093/jnci/djr491.

Nishikawa, R.M., Schmidt, R.A., Linver, M.N., Edwards, A.V., Papaioannou, J., & Stull, M.A. (2012). Clinically Missed Cancer: How Effectively Can Radiologists Use Computer-Aided Detection?. AMERICAN JOURNAL OF ROENTGENOLOGY, 198(3), 708-716.American Roentgen Ray Society. doi: 10.2214/AJR.11.6423.

Reiser, I., Nishikawa, R.M., Giger, M.L., Boone, J.M., Lindfors, K.K., & Yang, K. (2012). Automated detection of mass lesions in dedicated breast CT: A preliminary study. MEDICAL PHYSICS, 39(2), 866-873.Wiley. doi: 10.1118/1.3678991.

Jing, H., Yang, Y., & Nishikawa, R.M. (2011). Detection of clustered microcalcifications using spatial point process modeling. PHYSICS IN MEDICINE AND BIOLOGY, 56(1), 1-17.IOP Publishing. doi: 10.1088/0031-9155/56/1/001.

Nishikawa, R.M. (2011). Mammographic Features of Breast Cancers at Single Reading with Computer-aided Detection and at Double Reading in a Large Multicenter Prospective Trial of Computer-aided Detection: CADET II. Breast Diseases: A Year Book Quarterly, 22(2), 139-140.Elsevier BV. doi: 10.1016/j.breastdis.2011.03.030.

Nishikawa, R.M., & Pesce, L.L. (2011). Fundamental limitations in developing computer-aided detection for mammography. NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 648(SUPPL. 1), S251-S254.Elsevier BV. doi: 10.1016/j.nima.2010.11.086.

Reiser, I., Lee, S., & Nishikawa, R.M. (2011). On the orientation of mammographic structure. MEDICAL PHYSICS, 38(10), 5303-5306.Wiley. doi: 10.1118/1.3633905.

Lubinsky, A.R., Johnson, J.A., Schweizer, S., Weber, J.K.R., Nishikawa, R.M., Domenicali, P., & Fantone, S.D. (2010). Scanning translucent glass-ceramic x-ray storage phosphors. Proc SPIE Int Soc Opt Eng, 7622(PART 3), 76223W.SPIE. doi: 10.1117/12.843346.

Oto, A., Kulkarni, K., Nishikawa, R., & Baron, R.L. (2010). Contrast enhancement of hepatic hemangiomas on multiphase MDCT: Can we diagnose hepatic hemangiomas by comparing enhancement with blood pool?. AJR Am J Roentgenol, 195(2), 381-386.American Roentgen Ray Society. doi: 10.2214/AJR.09.3324.

Reiser, I., & Nishikawa, R.M. (2010). Task-based assessment of breast tomosynthesis: Effect of acquisition parameters and quantum noise. MEDICAL PHYSICS, 37(4), 1591-1600.Wiley. doi: 10.1118/1.3357288.

Engstrom, E., Reiser, I., & Nishikawa, R. (2009). Comparison of power spectra for tomosynthesis projections and reconstructed images. Med Phys, 36(5), 1753-1758.Wiley. doi: 10.1118/1.3116774.

Nishikawa, R.M., & Pesce, L.L. (2009). Computer-aided Detection Evaluation Methods Are Not Created Equal. RADIOLOGY, 251(3), 634-636.Radiological Society of North America (RSNA). doi: 10.1148/radiol.2513081130.

Nishikawa, R.M., Acharyya, S., Gatsonis, C., Pisano, E.D., Cole, E.B., Marques, H.S., D'Orsi, C.J., Farria, D.M., Kanal, K.M., Mahoney, M.C., Rebner, M., Staiger, M.J., & Screenin, D.M.I. (2009). Comparison of Soft-copy and Hard-copy Reading for Full-Field Digital Mammography. RADIOLOGY, 251(1), 41-49.Radiological Society of North America (RSNA). doi: 10.1148/radiol.2511071462.

Sidky, E.Y., Pan, X., Reiser, I.S., Nishikawa, R.M., Moore, R.H., & Kopans, D.B. (2009). Enhanced imaging of microcalcifications in digital breast tomosynthesis through improved image-reconstruction algorithms. MEDICAL PHYSICS, 36(11), 4920-4932.Wiley. doi: 10.1118/1.3232211.

Wei, L., Yang, Y., & Nishikawa, R.M. (2009). Microcalcification classification assisted by content-based image retrieval for breast cancer diagnosis. PATTERN RECOGNITION, 42(6), 1126-1132.Elsevier BV. doi: 10.1016/j.patcog.2008.08.028.

Wei, L., Yang, Y., Wernick, M.N., & Nishikawa, R.M. (2009). Learning of Perceptual Similarity From Expert Readers for Mammogram Retrieval. IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 3(1), 53-61.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/JSTSP.2008.2011159.

Reiser, I., Nishikawa, R.M., Edwards, A.V., Kopans, D.B., Schmidt, R.A., Papaioannou, J., & Moore, R.H. (2008). Automated detection of microcalcification clusters for digital breast tomosynthesis using projection data only: A preliminary study. MEDICAL PHYSICS, 35(4), 1486-1493.Wiley. doi: 10.1118/1.2885366.

Nishikawa, R.M. (2007). Current status and future directions of computer-aided diagnosis in mammography. Comput Med Imaging Graph, 31(4-5), 224-235.Elsevier BV. doi: 10.1016/j.compmedimag.2007.02.009.

Nishikawa, R.M., Schmidt, R.A., & Metz, C.E. (2007). Computer-aided screening mammography. NEW ENGLAND JOURNAL OF MEDICINE, 357(1), 84.

Rana, R.S., Jiang, Y., Schmidt, R.A., & Nishikawa, R.M. (2007). Independent evaluation of computer classification of malignant and benign calcifications in full-field digital mammograms. ACADEMIC RADIOLOGY, 14(3), 363-370.Elsevier BV. doi: 10.1016/j.acra.2006.12.012.

Chen, G., Johnson, J., Weber, R., Nishikawa, R., Schweizer, S., Newman, P., & MacFarlane, D. (2006). Fluorozirconate-based nanophase glass ceramics for high-resolution medical X-ray imaging. Journal of Non-Crystalline Solids, 352(6-7), 610-614.Elsevier BV. doi: 10.1016/j.jnoncrysol.2005.11.048.

Jiang, Y., Metz, C.E., Nishikawa, R.M., & Schmidt, R.A. (2006). Comparison of Independent Double Readings and Computer-Aided Diagnosis (CAD) for the Diagnosis of Breast Calcifications. Academic Radiology, 13(4), 534-535.Elsevier BV. doi: 10.1016/j.acra.2006.02.048.

Jiang, Y.L., Metz, C.E., Nishikawa, R.M., & Schmidt, R.A. (2006). Comparison of independent double readings and computer-aided diagnosis (CAD) for the diagnosis of breast calcifications. ACADEMIC RADIOLOGY, 13(1), 84-94.Elsevier BV. doi: 10.1016/j.acra.2005.09.086.

Nishikawa, R.M., Edwards, A.V., Schmidt, R.A., Papaioannou, J., & Linver, M.N. (2006). Measuring radiologists' ability to recognized correct computer prompts. INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, 1(SUPPL. 7), 329-330.

Nishikawa, R.M., Kallergi, M., & Orton, C.G. (2006). Computer-aided detection, in its present form, is not an effective aid for screening mammography. MEDICAL PHYSICS, 33(4), 811-814.Wiley. doi: 10.1118/1.2168063.

Reiser, I., & Nishikawa, R. (2006). Computerized Mass Detection for Digital Breast Tomosynthesis. In Recent Advances in Breast Imaging, Mammography, and Computer-Aided Diagnosis of Breast Cancer. (pp. 409-428).SPIE. doi: 10.1117/3.651880.ch12.

Reiser, I., & Nishikawa, R.M. (2006). Identification of simulated microcalcifications in white noise and mammographic backgrounds. MEDICAL PHYSICS, 33(8), 2905-2911.Wiley. doi: 10.1118/1.2210566.

Reiser, I., Nishikawa, R.M., Giger, M.L., Wu, T., Rafferty, E.A., Moore, R., & Kopans, D.B. (2006). Computerized mass detection for digital breast tomosynthesis directly from the projection images. MEDICAL PHYSICS, 33(2), 482-491.Wiley. doi: 10.1118/1.2163390.

Suri, J., Chandrasekhar, R., Lanconelli, N., Campanini, R., Roffilli, M., Chang, R.F., Guo, Y., Sivaramakrishna, R., Tot, T., Acha, B., Serrano, C., Reiser, I., Nishikawa, R., Wu, D., Wong, K.P., Kshirsagar, A., Sun, Y., Wirth, M., Cao, A., Desautels, J.E., & Rangayyan, R. (2006). The Current Status and Likely Future of Breast Imaging CAD. In Recent Advances in Breast Imaging, Mammography, and Computer-Aided Diagnosis of Breast Cancer. (pp. 901-961).SPIE. doi: 10.1117/3.651880.ch28.

Edwards, D.C., Metz, C.E., & Nishikawa, R.M. (2005). The hypervolume under the ROC hypersurface of "near-guessing" and "near-perfect" observers in N-class classification tasks. IEEE Trans Med Imaging, 24(3), 293-299.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/tmi.2004.841227.

Nishikawa, R. (2005). TU-D-I-609-02: What to Expect When CAD Is Implemented Clinically. Medical Physics, 32(6Part16), 2093-2094.Wiley. doi: 10.1118/1.1999708.

Nishikawa, R. (2005). TU-D-I-609-01: Overview. Medical Physics, 32(6Part16), 2093.Wiley. doi: 10.1118/1.1998388.

Reiser, I., Nishikawa, R., Giger, M., Rafferty, E., Moore, R., Kopans, D., & Wu, T. (2005). SU-EE-A2-02: Efficient Automatic Pre-Selection of Mass Lesion Candidates in DBT Breast Volumes. Medical Physics, 32(6Part2), 1897.Wiley. doi: 10.1118/1.1997454.

Reiser, I., Nishikawa, R.M., Giger, M.L., Kopans, D.B., Rafferty, E.A., Wu, T., & Moore, R. (2005). A multi-scale 3D radial gradient filter for computerized mass detection in digital tomosynthesis breast images. International Congress Series, 1281, 1058-1062.Elsevier BV. doi: 10.1016/j.ics.2005.03.171.

Wei, L., Yang, Y., Nishikawa, R.M., & Jiang, Y. (2005). A study on several machine-learning methods for classification of malignant and benign clustered microcalcifications. IEEE Trans Med Imaging, 24(3), 371-380.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/tmi.2004.842457.

Wei, L.Y., Yang, Y.Y., Nishikawa, R.M., Wernick, M.N., & Edwards, A. (2005). Relevance vector machine for automatic detection of clustered microcalcifications. IEEE TRANSACTIONS ON MEDICAL IMAGING, 24(10), 1278-1285.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TMI.2005.855435.

Edwards, D.C., Lan, L., Metz, C.E., Giger, M.L., & Nishikawa, R.M. (2004). Estimating three-class ideal observer decision variables for computerized detection and classification of mammographic mass lesions. MEDICAL PHYSICS, 31(1), 81-90.Wiley. doi: 10.1118/1.1631912.

El-Naqa, I., Yang, Y.Y., Galatsanos, N.P., Nishikawa, R.M., & Wernick, M.N. (2004). A similarity learning approach to content-based image retrieval: Application to digital mammography. IEEE TRANSACTIONS ON MEDICAL IMAGING, 23(10), 1233-1244.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TMI.2004.834601.

Paquerault, S., Yarusso, L.M., Papaioannou, J., Jiang, Y.L., & Nishikawa, R.M. (2004). Radial gradient-based segmentation of mammographic microcalcifications: Observer evaluation and effect on CAD performance. MEDICAL PHYSICS, 31(9), 2648-2657.Wiley. doi: 10.1118/1.1767692.

Reiser, I., Nishikawa, R.M., Giger, M.L., Wu, T., Rafferty, E., Moore, R.H., & Kopans, D.B. (2004). Computerized detection of mass lesions in digital breast tomosynthesis images using two- and three dimensional radial gradient index segmentation. TECHNOLOGY IN CANCER RESEARCH & TREATMENT, 3(5), 437-441.SAGE Publications. doi: 10.1177/153303460400300504.

Wilkie, J.R., Giger, M.L., Chinander, M.R., Vokes, T.J., Nishikawa, R.M., & Carlin, M.D. (2004). Investigation of physical image quality indices of a bone densitometry system. MEDICAL PHYSICS, 31(4), 873-881.Wiley. doi: 10.1118/1.1650528.

Zhang, Y., & Nishikawa, R.M. (2004). Computer simulation of mammographic imaging for applications in CAD. International Congress Series, 1268(C), 890-895.Elsevier BV. doi: 10.1016/j.ics.2004.03.222.

Salfity, M.F., Nishikawa, R.M., Jiang, Y.L., & Papaioannou, J. (2003). The use of a priori information in the detection of mammographic microcalcifications to improve their classification. MEDICAL PHYSICS, 30(5), 823-831.Wiley. doi: 10.1118/1.1559884.

Beiden, S.V., Wagner, R.F., Doi, K., Nishikawa, R.M., Freedman, M., Ben Lo, S.C., & Xu, X.W. (2002). Independent versus sequential reading in ROC studies of computer-assist modalities: Analysis of components of variance. ACADEMIC RADIOLOGY, 9(9), 1036-1043.Elsevier BV. doi: 10.1016/S1076-6332(03)80479-8.

Edwards, D.C., Kupinski, M.A., Metz, C.E., & Nishikawa, R.M. (2002). Maximum likelihood fitting of FROC curves under an initial-detection-and-candidate-analysis model. MEDICAL PHYSICS, 29(12), 2861-2870.Wiley. doi: 10.1118/1.1524631.

El-Naqa, I., Yang, Y.Y., Wernick, M.N., Galatsanos, N.P., & Nishikawa, R.M. (2002). A support vector machine approach for detection of microcalcifications. IEEE TRANSACTIONS ON MEDICAL IMAGING, 21(12), 1552-1563.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TMI.2002.806569.

Nishikawa, R. (2002). Assessment of the performance of computer-aided diagnosis and computer-aided diagnosis systems. Seminars in Breast Disease, 5(4), 217-222.

Jiang, Y.L., Nishikawa, R.M., & Papaioannou, J. (2001). Dependence of computer classification of clustered microcalcifications on the correct detection of microcalcifications. MEDICAL PHYSICS, 28(9), 1949-1957.Wiley. doi: 10.1118/1.1397715.

Jiang, Y.L., Nishikawa, R.M., Schmidt, R.A., Toledano, A.Y., & Doi, K. (2001). Potential of computer-aided diagnosis to reduce variability in radiologists' interpretations of mammograms depicting microcalcifications. RADIOLOGY, 220(3), 787-794.Radiological Society of North America (RSNA). doi: 10.1148/radiol.220001257.

Nishikawa, R.M. (2001). Evaluation of computer-aided detection and computer detection systems. Applied Radiology, 30(11 SUPPL.), 14-16.

Pisano, E.D., Cole, E.B., Major, S., Zong, S.Q., Hemminger, B.M., Muller, K.E., Johnston, R.E., Walsh, R., Conant, E., Fajardo, L.L., Feig, S.A., Nishikawa, R.M., Yaffe, M.J., Williams, M.B., Aylward, S.R., & Grp, I.D.M.D. (2000). Radiologists' preferences for digital mammographic display. RADIOLOGY, 216(3), 820-830.Radiological Society of North America (RSNA). doi: 10.1148/radiology.216.3.r00se48820.

Vyborny, C.J., Giger, M.L., & Nishikawa, R.M. (2000). Computer-aided detection and diagnosis of breast cancer. RADIOLOGIC CLINICS OF NORTH AMERICA, 38(4), 725-+.Elsevier BV. doi: 10.1016/S0033-8389(05)70197-4.

Anastasio, M.A., Kupinski, M.A., Nishikawa, R.M., & Giger, M.L. (1999). Multiobjective approach to optimizing compterized detection schemes. IEEE Nuclear Science Symposium and Medical Imaging Conference, 3, 1879-1883.

Doi, K., MacMahon, H., Katsuragawa, S., Nishikawa, R.M., & Jiang, Y.L. (1999). Computer-aided diagnosis in radiology: potential and pitfalls. EUROPEAN JOURNAL OF RADIOLOGY, 31(2), 97-109.Elsevier BV. doi: 10.1016/S0720-048X(99)00016-9.

Hamed, S.S., Gleason, S.S., & Nishikawa, R.M. (1999). Front-end data reduction in computer-aided diagnosis of mammograms: A pilot study. Proceedings of SPIE - The International Society for Optical Engineering, 3661(II), 1535-1543.

Jiang, Y., & Nishikawa, R.M. (1999). Radiologists' ability of using computer-aided diagnosis (CAD) to improve breast biopsy recommendations. Proceedings of SPIE - The International Society for Optical Engineering, 3663, 56-60.

Jiang, Y.L., Nishikawa, R.M., Schmidt, R.A., Metz, C.E., Giger, M.L., & Doi, K. (1999). Improving breast cancer diagnosis with computer-aided diagnosis. ACADEMIC RADIOLOGY, 6(1), 22-33.Elsevier BV. doi: 10.1016/S1076-6332(99)80058-0.

Nishikawa, R.M. (1999). Computer-aided diagnosis complements full-field digital mammography. Diagn Imaging (San Franc), 21(9), 47-75.

Anastasio, M.A., Yoshida, H., Nagel, R., Nishikawa, R.M., & Doi, K. (1998). A genetic algorithm-based method for optimizing the performance of a computer-aided diagnosis scheme for detection of clustered microcalcifications in mammograms. MEDICAL PHYSICS, 25(9), 1613-1620.Wiley. doi: 10.1118/1.598341.

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Jiang, Y., Nishikawa, R.M., Wolverton, D.E., Metz, C.E., Schmidt, R.A., & Doi, K. (1997). Computerized classification of malignant and benign clustered microcalcifications in mammograms. Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, 2, 521-523.

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EMA, T., DOI, K., NISHIKAWA, R.M., JIANG, Y.L., & PAPAIOANNOU, J. (1995). IMAGE FEATURE ANALYSIS AND COMPUTER-AIDED DIAGNOSIS IN MAMMOGRAPHY - REDUCTION OF FALSE-POSITIVE CLUSTERED MICROCALCIFICATIONS USING LOCAL EDGE-GRADIENT ANALYSIS. MEDICAL PHYSICS, 22(2), 161-169.Wiley. doi: 10.1118/1.597465.

METZ, C.E., WAGNER, R.F., DOI, K., BROWN, D.G., NISHIKAWA, R.M., & MYERS, K.J. (1995). TOWARD CONSENSUS ON QUANTITATIVE ASSESSMENT OF MEDICAL IMAGING-SYSTEMS. MEDICAL PHYSICS, 22(7), 1057-1061.Wiley. doi: 10.1118/1.597511.

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Schmidt, R.A., & Nishikawa, R.M. (1995). Clinical use of digital mammography: the present and the prospects. J Digit Imaging, 8(1 Suppl 1), 74-79.Springer Science and Business Media LLC. doi: 10.1007/BF03168072.

Hoffmann, K.R., Doi, K., MacMahon, H., Giger, M.L., Nishikawa, R.M., Xu, X.W., Yao, L., Kano, A., & Carlin, M. (1994). Development of a digital duplication system for portable chest radiographs. J Digit Imaging, 7(3), 146-153.Springer Science and Business Media LLC. doi: 10.1007/BF03168508.

NISHIKAWA, R.M., GIGER, M.L., DOI, K., METZ, C.E., YIN, F.F., VYBORNY, C.J., & SCHMIDT, R.A. (1994). EFFECT OF CASE SELECTION ON THE PERFORMANCE OF COMPUTER-AIDED DETECTION SCHEMES. MEDICAL PHYSICS, 21(2), 265-269.Wiley. doi: 10.1118/1.597287.

ZHANG, W., DOI, K., GIGER, M.L., WU, Y.Z., NISHIKAWA, R.M., & SCHMIDT, R.A. (1994). COMPUTERIZED DETECTION OF CLUSTERED MICROCALCIFICATIONS IN DIGITAL MAMMOGRAMS USING A SHIFT-INVARIANT ARTIFICIAL NEURAL-NETWORK. MEDICAL PHYSICS, 21(4), 517-524.Wiley. doi: 10.1118/1.597177.

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Lee, J., & Nishikawa, R. (2020). Simulating breast mammogram using Conditional Generative Adversarial Network: application towards finding mammographically-occult cancer. In Medical Imaging 2020: Computer-Aided Diagnosis, 11314.SPIE. doi: 10.1117/12.2549093.

Lee, J., Nishikawa, R.M., & Rohde, G.K. (2018). Detecting mammographically occult cancer in women with dense breasts using Radon Cumulative Distribution Transform: a preliminary analysis. In Medical Imaging 2018: Computer-Aided Diagnosis, 10575.SPIE. doi: 10.1117/12.2293541.

Yang, Y., Nishikawa, R.M., & Sainz de Cea, M.V. (2018). Reducing the effect of false positives in classification of detected clustered microcalcifications. In 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), 2018-April, (pp. 253-256).IEEE. doi: 10.1109/isbi.2018.8363567.

Lee, J., Nishikawa, R.M., Reiser, I., & Boone, J.M. (2017). Neutrosophic segmentation of breast lesions for dedicated breast CT. In Medical Imaging 2017: Computer-Aided Diagnosis, 10134.SPIE. doi: 10.1117/12.2254128.

Marcomini, K.D., Fleury, E.F.C., Oliveira, V.M., Carneiro, A.A.O., Schiabel, H., & Nishikawa, R.M. (2017). Agreement between a computer-assisted tool and radiologists to classify lesions in breast elastography images. In Medical Imaging 2017: Computer-Aided Diagnosis, 10134.SPIE. doi: 10.1117/12.2255001.

Marcomini, K.D., Fleury, E.F.C., Oliveira, V.M., Carneiro, A.A.O., Schiabel, H., & Nishikawa, R.M. (2017). Agreement between a computer-assisted tool and radiologists to classify lesions in breast elastography images. In Proceedings of SPIE - The International Society for Optical Engineering, 10327.

Hakim, C.M., Bandos, A.I., Ganott, M.A., Catullo, V.J., Chough, D.M., Kelly, A.E., Shinde, D.D., Sumkin, J.H., Wallace, L.P., Nishikawa, R.M., & Gur, D. (2016). Changes in frequency of recall recommendations of examinations depicting cancer with the availability of either priors or digital breast tomosynthesis. In Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, 9787.SPIE. doi: 10.1117/12.2213075.

Lee, J., Nishikawa, R.M., Reiser, I., & Boone, J.M. (2016). Can model observers be developed to reproduce radiologists' diagnostic performances? Our study says not so fast!. In Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, 9787.SPIE. doi: 10.1117/12.2216253.

Marcomini, K.D., Fleury, E.F.C., Schiabel, H., & Nishikawa, R.M. (2016). Proposal of Semi-automatic Classification of Breast Lesions for Strain Sonoelastography Using a Dedicated CAD System. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9699, (pp. 454-460).Springer International Publishing. doi: 10.1007/978-3-319-41546-8_57.

Nishikawa, R.M., Comstock, C.E., Linver, M.N., Newstead, G.M., Sandhir, V., & Schmidt, R.A. (2016). Agreement Between Radiologists’ Interpretations of Screening Mammograms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9699, (pp. 3-10).Springer International Publishing. doi: 10.1007/978-3-319-41546-8_1.

Wang, J., Yang, Y., & Nishikawa, R.M. (2016). Quantitative study of image features of clustered microcalcifications in for-presentation mammograms. In 2016 IEEE International Conference on Image Processing (ICIP), 2016-August, (pp. 3404-3408).IEEE. doi: 10.1109/icip.2016.7532991.

Wang, J., Yang, Y., Wernick, M.N., & Nishikawa, R.M. (2016). An image-retrieval aided diagnosis system for clustered microcalcifications. In 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 2016-June, (pp. 1076-1079).IEEE. doi: 10.1109/isbi.2016.7493452.

Nishikawa, R.M., & Bandos, A. (2014). Predicting the Benefit of Using CADe in Screening Mammography. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8539 LNCS, (pp. 44-49).Springer International Publishing. doi: 10.1007/978-3-319-07887-8_7.

Sidky, E.Y., Reiser, I.S., Nishikawa, R.M., & Pan, X. (2014). Enhancing tissue structures with iterative image reconstruction for digital breast tomosynthesis. In Medical Imaging 2014: Physics of Medical Imaging, 9033.SPIE. doi: 10.1117/12.2043776.

Wang, J., Yang, Y., Wernick, M.N., & Nishikawa, R.M. (2014). Exploring perceptually similar cases with multi-dimensional scaling. In Medical Imaging 2014: Computer-Aided Diagnosis, 9035.SPIE. doi: 10.1117/12.2043600.

Chen, X., Nishikawa, R.M., & Mou, X. (2013). Conventional mammographic image generation in dual-energy digital mammography. In Medical Imaging 2013: Physics of Medical Imaging, 8668.SPIE. doi: 10.1117/12.2007828.

Reiser, I., Sidky, E.Y., Nishikawa, R.M., Yang, K., Boone, J.M., & Pan, X. (2013). Fast, robust dynamic field-of-view adjustment for iterative reconstruction of dedicated breast CT. In 2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (2013 NSS/MIC).IEEE. doi: 10.1109/nssmic.2013.6829370.

Siewerdsen, J., Nishikawa, R., Cunningham, I., Chen, G., & Bochud, F. (2013). TU-E-103-01: Image Quality Models in Advanced CT Applications. In Medical Physics, 40(6Part27), (pp. 449-450).Wiley. doi: 10.1118/1.4815440.

Wang, J., Yang, Y., & Nishikawa, R.M. (2013). Reduction of false positive detection in clustered microcalcifications. In 2013 IEEE International Conference on Image Processing, (pp. 1433-1437).IEEE. doi: 10.1109/icip.2013.6738294.

Chen, X., Nishikawa, R.M., Chan, S.T., Lau, B.A., Zhang, L., & Mou, X. (2012). Algorithmic scatter correction in dual-energy digital mammography for calcification imaging. In Medical Imaging 2012: Physics of Medical Imaging, 8313.SPIE. doi: 10.1117/12.911775.

Nishikawa, R.M. (2012). Estimating Sensitivity and Specificity in an ROC Experiment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7361 LNCS, (pp. 690-696).Springer Berlin Heidelberg. doi: 10.1007/978-3-642-31271-7_89.

Nishikawa, R.M. (2012). Methods for Evaluating the Effectiveness of Screening Mammography Are Not Necessarily Valid for Evaluating the Effectiveness of Computer-Aided Detection in Screening Mammography. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7361 LNCS, (pp. 705-712).Springer Berlin Heidelberg. doi: 10.1007/978-3-642-31271-7_91.

Nishikawa, R.M. (2012). Fortieth anniversary of spie medical imaging meeting. In Proceedings of SPIE - The International Society for Optical Engineering, 8425.

Reiser, I., & Nishikawa, R.M. (2012). Signal-known exactly detection performance in tomosynthesis: does volume visualization help human observers?. In Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment, 8318.SPIE. doi: 10.1117/12.913559.

Reiser, I., Lau, B.A., Nishikawa, R.M., & Bakic, P.R. (2012). A Directional Small-Scale Tissue Model for an Anthropomorphic Breast Phantom. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7361 LNCS, (pp. 141-148).Springer Berlin Heidelberg. doi: 10.1007/978-3-642-31271-7_19.

Reiser, I., Lu, Z., & Nishikawa, R. (2012). TH-E-217BCD-01: Contrast-To-Noise Ratio Is Not an Appropriate Measure of CT Image Quality When Comparing Different Iterative Reconstruction Algorithms. In Medical Physics, 39(6Part31), (p. 4014).Wiley. doi: 10.1118/1.4736374.

SPIE, P.O. (2012). Front Matter: Volume 8315. In Medical Imaging 2012: Computer-Aided Diagnosis, 8315.SPIE. doi: 10.1117/12.931426.

SPIE, P.O. (2012). Front Matter: Volume 8313. In Medical Imaging 2012: Physics of Medical Imaging, 8313.SPIE. doi: 10.1117/12.945882.

Chen, X., Nishikawa, R.M., Chan, S.T., Zhang, L., & Mou, X. (2011). Image noise sensitivity of dual-energy digital mammography for calcification imaging. In Medical Imaging 2011: Physics of Medical Imaging, 7961.SPIE. doi: 10.1117/12.877932.

Jing, H., Yang, Y., Wernick, M.N., Yarusso, L.M., & Nishikawa, R.M. (2011). A comparison study of textural features between FFDM and film mammogram images. In Medical Imaging 2011: Computer-Aided Diagnosis, 7963.SPIE. doi: 10.1117/12.877577.

Jing, H., Yang, Y., Yarusso, L.M., & Nishikawa, R.M. (2011). Textural feature comparison between FFDM and film mammograms. In 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, (pp. 148-151).IEEE. doi: 10.1109/isbi.2011.5872375.

Lau, B.A., Reiser, I., & Nishikawa, R.M. (2011). Issues in characterizing anatomic structure in digital breast tomosynthesis. In Medical Imaging 2011: Physics of Medical Imaging, 7961.SPIE. doi: 10.1117/12.878871.

Nishikawa, R., Glick, S., Bakic, P., & Reiser, I. (2011). MO-A-214-01: 3D Breast Models. In Medical Physics, 38(6Part25), (p. 3706).Wiley. doi: 10.1118/1.3612892.

Bakic, P.R., Lau, B., Carton, A.K., Reiser, I., Maidment, A.D.A., & Nishikawa, R.M. (2010). An Anthropomorphic Software Breast Phantom for Tomosynthesis Simulation: Power Spectrum Analysis of Phantom Projections. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6136 LNCS, (pp. 452-458).Springer Berlin Heidelberg. doi: 10.1007/978-3-642-13666-5_61.

Lau, B., Bakic, P., Reiser, I., Carton, A.K., Maidment, A., & Nishikawa, R. (2010). TH-D-201B-08: An Anthropomorphic Software Breast Phantom for Tomosynthesis Simulation: Power Spectrum Analysis of Phantom Reconstructions. In Medical Physics, 37(6Part7), (p. 3473).Wiley. doi: 10.1118/1.3469567.

Nishikawa, R.M., & Pesce, L.L. (2010). Stratified Sampling for Case Selection Criteria for Evaluating CAD. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6136 LNCS, (pp. 534-539).Springer Berlin Heidelberg. doi: 10.1007/978-3-642-13666-5_72.

Nishikawa, R.M., Jiang, Y., & Metz, C.E. (2010). Rating scales for observer performance studies. In Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment, 7627.SPIE. doi: 10.1117/12.844993.

Reiser, I., & Nishikawa, R.M. (2010). Human Observer Performance in a Single Slice or a Volume: Effect of Background Correlation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6136 LNCS, (pp. 327-333).Springer Berlin Heidelberg. doi: 10.1007/978-3-642-13666-5_44.

Reiser, I., Joseph, S.P., Nishikawa, R.M., Giger, M.L., Boone, J., Lindfors, K., Edwards, A., Packard, N., Moore, R.H., & Kopans, D.B. (2010). Evaluation of a 3D lesion segmentation algorithm on DBT and breast CT images. In Medical Imaging 2010: Computer-Aided Diagnosis, 7624.SPIE. doi: 10.1117/12.844484.

Reiser, I., Lee, S., Little, K., & Nishikawa, R.M. (2010). Toward validation of a 3D structured background model for breast imaging. In Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment, 7627.SPIE. doi: 10.1117/12.844692.

Reiser, I.S., Nishikawa, R.M., & Lau, B.A. (2009). Effect of non-isotropic detector blur on microcalcification detectability in tomosynthesis. In Medical Imaging 2009: Physics of Medical Imaging, 7258.SPIE. doi: 10.1117/12.813808.

Fredenberg, E., Cederström, B., Lundqvist, M., Ribbing, C., Åslund, M., Diekmann, F., Nishikawa, R., & Danielsson, M. (2008). Contrast-enhanced dual-energy subtraction imaging using electronic spectrum-splitting and multi-prism x-ray lenses. In Medical Imaging 2008: Physics of Medical Imaging, 6913.SPIE. doi: 10.1117/12.770501.

Lau, B., Reiser, I., & Nishikawa, R. (2008). TH-C-332-09: The Effect of Variable Exposure Distribution On Microcalcification Detectability in Tomosynthesis. In Medical Physics, 35(6Part26), (p. 2978).Wiley. doi: 10.1118/1.2962875.

Lau, B.A., Reiser, I.S., & Nishikawa, R.M. (2008). Microcalcification detectability in tomosynthesis. In Medical Imaging 2008: Physics of Medical Imaging, 6913.SPIE. doi: 10.1117/12.773076.

Reiser, I., Lau, B.A., & Nishikawa, R.M. (2008). Effect of Scan Angle and Reconstruction Algorithm on Model Observer Performance in Tomosynthesis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5116 LNCS, (pp. 606-611).Springer Berlin Heidelberg. doi: 10.1007/978-3-540-70538-3_84.

Sidky, E.Y., Reiser, I., Nishikawa, R.M., Pan, X., Chartrand, R., Kopans, D.B., & Moore, R.H. (2008). Practical iterative image reconstruction in digital breast tomosynthesis by non-convex TpV optimization. In Medical Imaging 2008: Physics of Medical Imaging, 6913.SPIE. doi: 10.1117/12.772796.

Sidky, E.Y., Reiser, I.S., Nishikawa, R.M., & Pan, X. (2008). Preliminary study on the impact of digital breast tomosynthesis scanning angle on micro-calcification imaging. In 2008 IEEE Nuclear Science Symposium Conference Record, (pp. 4201-4204).IEEE. doi: 10.1109/nssmic.2008.4774208.

Yarusso, L.M., & Nishikawa, R.M. (2008). Influence of signal-to-noise ratio and temporal stability on computer-aided detection of mammographic microcalcifications in digitized screen-film and full-field digital mammography. In Medical Imaging 2008: Computer-Aided Diagnosis, 6915.SPIE. doi: 10.1117/12.773069.

Chinander, M.R., Nishikawa, R.M., & Seifi, P. (2007). Observer evaluation of a method for producing simulated mammograms. In Medical Imaging 2007: Physics of Medical Imaging, 6510(PART 1).SPIE. doi: 10.1117/12.713862.

Nishikawa, R.M., Reiser, I., Seifi, P., & Vyborny, C.J. (2007). A new approach to digital breast tomosynthesis for breast cancer screening. In Medical Imaging 2007: Physics of Medical Imaging, 6510(PART 2).SPIE. doi: 10.1117/12.713677.

Reiser, I., Nishikawa, R.M., Sidky, E.Y., Chinander, M.R., & Seifi, P. (2007). Development of a model for breast tomosynthesis image acquisition. In Medical Imaging 2007: Physics of Medical Imaging, 6510(PART 2).SPIE. doi: 10.1117/12.713752.

Sidky, E.Y., Reiser, I.S., Nishikawa, R., & Pan, X. (2007). Image reconstruction in digital breast tomosynthesis by total variation minimization. In Medical Imaging 2007: Physics of Medical Imaging, 6510(PART 2).SPIE. doi: 10.1117/12.713663.

Li, H., Giger, M.L., Yuan, Y., Lan, L., Suzuki, K., Jamieson, A., Yarusso, L., Nishikawa, R.M., & Sennett, C. (2006). Comparison of computerized image analyses for digitized screen-film mammograms and full-field digital mammography images. In DIGITAL MAMOGRAPHY, PROCEEDINGS, 4046, (pp. 569-575).Springer Berlin Heidelberg. doi: 10.1007/11783237_77.

Nishikawa, R. (2006). WE-C-330D-02: Image Science and CAD: In Pursuit of a Fundamental Theoretical Basis for CAD Development. In Medical Physics, 33(6Part19), (p. 2231).Wiley. doi: 10.1118/1.2241689.

Nishikawa, R.M. (2006). Modeling the effect of computer-aided detection on the sensitivity of screening mammography. In DIGITAL MAMOGRAPHY, PROCEEDINGS, 4046, (pp. 46-53).Springer Berlin Heidelberg. doi: 10.1007/11783237_7.

Nishikawa, R.M., Edwards, A., Schmidt, R.A., Papaioannou, J., & Linver, M.N. (2006). Can radiologists recognize that a computer has identified cancers that they have overlooked?. In Medical Imaging 2006: Image Perception, Observer Performance, and Technology Assessment, 6146.SPIE. doi: 10.1117/12.656351.

Reiser, I., Sidky, E.Y., Nishikawa, R.M., & Pan, X. (2006). Development of an analytic breast phantom for quantitative comparison of reconstruction algorithms for digital breast tomosynthesis. In DIGITAL MAMOGRAPHY, PROCEEDINGS, 4046, (pp. 190-196).Springer Berlin Heidelberg. doi: 10.1007/11783237_27.

Wei, L., Yang, Y., Nishikawa, R.M., & Wernick, M.N. (2006). Mammogram Retrieval by Similarity Learning from Experts. In 2006 International Conference on Image Processing, (pp. 2517-2520).IEEE. doi: 10.1109/icip.2006.312805.

Wei, L., Yang, Y., Nishikawa, R.M., & Wernick, M.N. (2006). Learning of perceptual similarity from expert readers for mammogram retrieval. In 2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings, 2006, (pp. 1356-1359).

Liyang Wei, Yongyi Yang, & Nishikawa, R.M. (2005). Relevance vector machine learning for detection of microcalcifications in mammograms. In IEEE International Conference on Image Processing 2005, 1, (pp. 9-12).IEEE. doi: 10.1109/icip.2005.1529674.

Reiser, I., & Nishikawa, R.M. (2005). Human performance for detection and discrimination of simulated microcalcifications in mammographic backgrounds. In Medical Imaging 2005: Image Perception, Observer Performance, and Technology Assessment, 5749, (pp. 223-230).SPIE. doi: 10.1117/12.597010.

Wei, L., Yang, Y., & Nishikawa, R.M. (2005). A relevance vector machine technique for the automatic detection of clustered microcalcifications (Honorable Mention Poster Award). In Medical Imaging 2005: Image Processing, 5747(II), (pp. 831-839).SPIE. doi: 10.1117/12.594828.

Wei, L., Yang, Y., Nishikawa, R.M., & Jiang, Y. (2005). A study of several CAD methods for classification of clustered microcalcifications. In Medical Imaging 2005: Image Processing, 5747(I), (pp. 1-8).SPIE. doi: 10.1117/12.594734.

Drukker, K., Edwards, D.C., Giger, M.L., Nishikawa, R.M., & Metz, C.E. (2004). Computerized detection and 3-way classification of breast lesions on ultrasound images. In Medical Imaging 2004: Image Processing, 5370 II, (pp. 1034-1041).SPIE. doi: 10.1117/12.534339.

Edwards, D.C., Metz, C.E., & Nishikawa, R.M. (2004). Hypervolume under the ROC hypersurface of a near-guessing ideal observer in a three-class classification task. In Medical Imaging 2004: Image Perception, Observer Performance, and Technology Assessment, 5(26), (pp. 128-137).SPIE. doi: 10.1117/12.536068.

Jiang, Y., Schmidt, R.A., Nishikawa, R.M., D'Orsi, C.J., Vyborny, C.J., & Newstead, G.M. (2004). Use of BI-RADS lesion descriptors in computer-aided diagnosis of malignant and benign breast lesions. In Medical Imaging 2004: Image Perception, Observer Performance, and Technology Assessment, 5(26), (pp. 199-202).SPIE. doi: 10.1117/12.537183.

Nishikawa, R.M., Yang, Y., Huo, D., Wernick, M., Sennett, C.A., Papaioannou, J., & Wei, L. (2004). Observers' ability to judge the similarity of clustered calcifications on mammograms. In Medical Imaging 2004: Image Perception, Observer Performance, and Technology Assessment, 5(26), (pp. 192-198).SPIE. doi: 10.1117/12.536571.

Reiser, I., Metz, C.E., & Nishikawa, R.M. (2004). Human efficiency in the detection and discrimination tasks. In Medical Imaging 2004: Image Perception, Observer Performance, and Technology Assessment, 5(26), (pp. 166-172).SPIE. doi: 10.1117/12.536214.

Reiser, I.S., Sidky, E.Y., Giger, M.L., Nishikawa, R.M., Rafferty, E.A., Kopans, D.B., Moore, R., & Wu, T. (2004). A reconstruction-independent method for computerized mass detection in digital tomosynthesis images of the breast. In Medical Imaging 2004: Image Processing, 5370 II, (pp. 833-838).SPIE. doi: 10.1117/12.535901.

Edwards, D.C., Lan, L., Metz, C.E., Giger, M.L., & Nishikawa, R.M. (2003). Bayesian ANN estimates of three-class ideal observer decision variables for classification of mammographic masses. In Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment, 5034, (pp. 474-482).SPIE. doi: 10.1117/12.480343.

Jiang, Y., Salfity, M.F., Chen, V., Nishikawa, R.M., Papaioannou, J., Edwards, A.V., & Paquerault, S. (2003). Effect of radiologists' variability on the performance of computer classification of malignant and benign clustered microcalcifications in mammograms. In Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment, 5034, (pp. 42-47).SPIE. doi: 10.1117/12.480360.

Maidment, A.D.A., Albert, M., Bunch, P.C., Cunningham, I.A., Dobbins III, J.T., Gagne, R.M., Nishikawa, R.M., Van Metter, R.L., & Wagner, R.F. (2003). Standardization of NPS measurement: interim report of AAPM TG16. In Medical Imaging 2003: Physics of Medical Imaging, 5030 I, (pp. 523-532).SPIE. doi: 10.1117/12.480451.

Nishikawa, R.M. (2003). Differences between mono- and poly-energetic spectra in modeling DQE(f). In Medical Imaging 2003: Physics of Medical Imaging, 5030 II, (pp. 871-876).SPIE. doi: 10.1117/12.480480.

Paquerault, S., Jiang, Y., Nishikawa, R.M., Schmidt, R.A., D'Orsi, C.J., Vyborny, C.J., & Newstead, G.M. (2003). Automated selection of BI-RADS lesion descriptors for reporting calcifications in mammograms. In Medical Imaging 2003: Image Processing, 5032 II, (pp. 802-809).SPIE. doi: 10.1117/12.480847.

Beiden, S.V., Wagner, R.F., Doi, K., Nishikawa, R.M., Freedman, M.T., Lo, S.C.B., & Xu, X.W. (2002). Independent versus sequential reading in ROC studies of computer-assist modalities. In Medical Imaging 2002: Image Perception, Observer Performance, and Technology Assessment, 4686, (pp. 198-204).SPIE. doi: 10.1117/12.462678.

Edwards, D.C., Metz, C.E., & Nishikawa, R.M. (2002). Estimation of three-class ideal observer decision functions with a Bayesian artificial neural network. In Medical Imaging 2002: Image Perception, Observer Performance, and Technology Assessment, 4686, (pp. 1-12).SPIE. doi: 10.1117/12.462662.

El-Naqa, I., Yang, Y., Wernick, M.N., Galatsanos, N.P., & Nishikawa, R. (2002). A support vector machine approach for detection of microcalcifications in mammograms. In IEEE International Conference on Image Processing, 2.

El-Naqa, I., Yongyi Yang, Wernick, M.N., Galatsanos, N.P., & Nishikawa, R. (2002). Support vector machine learning for detection of microcalcifications in mammograms. In Proceedings IEEE International Symposium on Biomedical Imaging, 2002-January, (pp. 201-204).IEEE. doi: 10.1109/isbi.2002.1029228.

Giger, M.L., Huo, Z., Vyborny, C.J., Lan, L., Bonta, I.R., Horsch, K., Nishikawa, R.M., & Rosenborough, I. (2002). Intelligent CAD workstation for breast imaging using similarity to known lesions and multiple visual prompt aids. In Medical Imaging 2002: Image Processing, 4684 II, (pp. 768-773).SPIE. doi: 10.1117/12.467222.

Nishikawa, R.M., Salfity, M.F., Jiang, Y., & Papaioannou, J. (2002). Improving the automated classification of clustered calcifications on mammograms through the improved detection of individual calcifications. In Medical Imaging 2002: Image Processing, 4684 III, (pp. 1339-1345).SPIE. doi: 10.1117/12.467097.

Beiden, S.V., Wagner, R.F., Campbell, G., Metz, C.E., Chan, H.P., Nishikawa, R.M., Schnall, M.D., & Jiang, Y. (2001). Analysis of components of variance in multiple-reader studies of computer-aided diagnosis with different tasks. In Medical Imaging 2001: Image Perception and Performance, 4324, (pp. 167-176).SPIE. doi: 10.1117/12.431185.

Edwards, D.C., Papaioannou, J., Jiang, Y., Kupinski, M.A., & Nishikawa, R.M. (2001). Eliminating false-positive microcalcification clusters in a mammography CAD scheme using a Bayesian neural network. In Medical Imaging 2001: Image Processing, 4322(3), (pp. 1954-1960).SPIE. doi: 10.1117/12.431089.

Nishikawa, R.M., Giger, M.L., Schmidt, R.A., & Papaioannou, J. (2001). Can computer-aided diagnosis (CAD) help radiologists find mammographically missed screening cancers?. In Medical Imaging 2001: Image Perception and Performance, 4324, (pp. 56-63).SPIE. doi: 10.1117/12.431172.

Valverde, F.L., Guil, N., Muñoz, J., Nishikawa, R., & Doi, K. (2001). An evaluation criterion for edge detection techniques in noisy images. In IEEE International Conference on Image Processing, 1, (pp. 766-769).

Edwards, D.C., Kupinski, M.A., Nishikawa, R.M., & Metz, C.E. (2000). Estimation of linear observer templates in the presence of multi-peaked Gaussian noise through 2AFC experiments. In Proceedings of SPIE - The International Society for Optical Engineering, 3981, (pp. 85-96).

Jiang, Y., Nishikawa, R.M., Schmidt, R.A., Metz, C.E., & Doi, K. (2000). Relative gains in diagnostic accuracy between computer-aided diagnosis and independent double reading. In Proceedings of SPIE - The International Society for Optical Engineering, 3981, (pp. 10-15).

Sajda, P., Spence, C., Parra, L., & Nishikawa, R. (2000). Hierarchical, multi-resolution models for object recognition: applications to mammographic computer-aided diagnosis. In Proceedings 29th Applied Imagery Pattern Recognition Workshop, 2000-January, (pp. 159-165).IEEE Comput. Soc. doi: 10.1109/aiprw.2000.953620.

Jiang, Y., Nishikawa, R.M., & Papaioannou, J. (1998). Requirement of microcalcification detection for computerized classification of malignant and benign clustered microcalcifications. In Medical Imaging 1998: Image Processing, 3338, (pp. 313-317).SPIE. doi: 10.1117/12.310907.

Nishikawa, R.M., & Yarusso, L.M. (1998). Variations in measured performance of CAD schemes due to database composition and scoring protocol. In Medical Imaging 1998: Image Processing, 3338, (pp. 840-844).SPIE. doi: 10.1117/12.310894.

Nishikawa, R.M., Wolverton, D.E., Schmidt, R.A., & Papaioannou, J. (1997). Radiologists' ability to discriminate computer-detected true and false positives from an automated scheme for the detection of clustered microcalcifications on digital mammograms. In Medical Imaging 1997: Image Perception, 3036, (pp. 198-204).SPIE. doi: 10.1117/12.271293.

Nishikawa, R.M., Papaioannou, J., & Collins, S.A. (1996). Reproducibility of an automated scheme for the detection of clustered microcalcifications on digital mammograms. In Medical Imaging 1996: Image Processing, 2710, (pp. 24-29).SPIE. doi: 10.1117/12.237942.

Sajda, P., Spence, C.D., Pearson, J.C., & Nishikawa, R.M. (1996). Exploiting context in mammograms: a hierarchical neural network for detecting microcalcifications. In Medical Imaging 1996: Image Processing, 2710, (pp. 733-742).SPIE. doi: 10.1117/12.237978.

Yoshida, H., Nishikawa, R.M., Giger, M.L., & Doi, K. (1996). Signal/background separation by wavelet packets for detection of microcalcifications in mammograms. In Wavelet Applications in Signal and Image Processing IV, 2825, (pp. 805-811).SPIE. doi: 10.1117/12.255304.

Nagel, R.H. (1995). Comparison of rule-based and artificial neural network approaches for improving the automated detection of clustered microcalcifications in mammograms. In Proceedings of SPIE, 2622(2), (pp. 775-779).SPIE. doi: 10.1117/12.216875.

Nishikawa, R.M., Haldemann, R.C., Papaioannou, J., Giger, M.L., Lu, P., Schmidt, R.A., Wolverton, D.E., Bick, U., & Doi, K. (1995). Initial experience with a prototype clinical intelligent mammography workstation for computer-aided diagnosis. In Medical Imaging 1995: Image Processing, 2434, (pp. 65-71).SPIE. doi: 10.1117/12.208732.

Yoshida, H., Zhang, W., Cai, W., Doi, K., Nishikawa, R.M., & Giger, M.L. (1995). Optimizing wavelet transform based on supervised learning for detection of microcalcifications in digital mammograms. In IEEE International Conference on Image Processing, 3, (pp. 152-155).

Jiang, Y., Nishikawa, R.M., Wolverton, D.E., Giger, M.L., Doi, K., Schmidt, R.A., & Vyborny, C.J. (1994). Mammographic feature analysis of clustered microcalcifications for classification of breast cancer and benign breast diseases. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, 16(pt 1), (pp. 594-595).

Nishikawa, R.M. (1994). Analysis of false-positive microcalcification clusters identified by a mammographic computer-aided detection scheme. In Proceedings of SPIE, 2167, (pp. 773-777).SPIE. doi: 10.1117/12.175115.

Yoshida, H., Doi, K., & Nishikawa, R.M. (1994). Automated detection of clustered microcalcifications in digital mammograms using wavelet processing techniques. In Medical Imaging 1994: Image Processing, 2167, (pp. 868-886).SPIE. doi: 10.1117/12.175126.

Doi, K., Giger, M., MacMahon, H., Nishikawa, R., Schmidt, R., Hoffmann, K., Katsuragawa, S., Sanada, S., Behlen, F., & Sluis, D. (1993). Development of Digital Processing Techniques for Computer-Aided Diagnosis in Radiographic Images. In Proceedings. The Third International Conference on Image Management and Communication in Patient Care, (pp. 110-115).IEEE. doi: 10.1109/imac.1993.665440.

Giger, M.L., Nishikawa, R.M., Schmidt, R.A., Vyborny, C.J., Lu, P., Jiang, Y., Huo, Z., Papaioannou, J., Wu, Y., Cox, S., Kunst, R., Bick, U., & Rosculet, K. (1993). Preliminary evaluation of an 'intelligent' mammography workstation. In Proceedings of SPIE - The International Society for Optical Engineering, 1898, (pp. 764-766).

Nishikawa, R.M. (1993). Design of a common database for research in mammogram image analysis. In Biomedical Image Processing and Biomedical Visualization, 1905, (pp. 548-549).SPIE. doi: 10.1117/12.148620.

Nishikawa, R.M., Giger, M.L., Doi, K., Vyborny, C.J., Schmidt, R.A., Metz, C.E., Wu, C.Y., Yin, F.F., Jiang, Y., Huo, Z., Lu, P., Zhang, W., Ema, T., Bick, U., Papaioannou, J., & Nagel, R.H. (1993). Computer-aided detection and diagnosis of masses and clustered microcalcifications from digital mammograms. In Biomedical Image Processing and Biomedical Visualization, 1905, (pp. 422-432).SPIE. doi: 10.1117/12.148655.

Nishikawa, R.M., Jiang, Y., Giger, M.L., Vyborny, C.J., Schmidt, R.A., & Bick, U. (1993). Characterization of the mammographic appearance of microcalcifications: applications in computer-aided diagnosis. In Proceedings of SPIE - The International Society for Optical Engineering, 1898, (pp. 422-429).

Jiang, Y., Nishikawa, R.M., Giger, M.L., Doi, K., Schmidt, R.A., & Vyborny, C.J. (1992). Method of extracting signal area and signal thickness of microcalcifications from digital mammograms. In Proceedings of SPIE - The International Society for Optical Engineering, 1778, (pp. 28-36).

Nishikawa, R.M., Jiang, Y., Giger, M.L., Doi, K., Vyborny, C.J., & Schmidt, R.A. (1992). Computer-aided detection of clustered microcalcifications. In [Proceedings] 1992 IEEE International Conference on Systems, Man, and Cybernetics, 1992-January, (pp. 1375-1378).IEEE. doi: 10.1109/icsmc.1992.271592.

Wu, Y., Giger, M.L., Doi, K., Metz, C.E., Nishikawa, R.M., Vyborny, C.J., & Schmidt, R.A. (1992). Application of artificial neural networks in mammography for the diagnosis of breast cancer. In Proceedings of SPIE - The International Society for Optical Engineering, 1778, (pp. 19-27).

Giger, M.L., Nishikawa, R.M., Doi, K., Yin, F.F., Vyborny, C.J., Schmidt, R.A., Metz, C.E., Wu, Y., MacMahon, H., & Yoshimura, H. (1991). Development of a 'smart' workstation for use in mammography. In Proceedings of SPIE - The International Society for Optical Engineering, 1445, (pp. 101-103).

Nishikawa, R.M., MacMahon, H., Doi, K., & Bosworth, E. (1991). Potential usefulness of a video printer for producing secondary images from digitized chest radiographs. In Proceedings of SPIE - The International Society for Optical Engineering, 1444, (pp. 180-189).

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