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Breast mass segmentation on dynamic contrast-enhanced magnetic resonance scans using the level set method.

J. Shi, B. Sahiner, H. Chan, C. Paramagul, L. Hadjiiski, M. Helvie, Y. Wu, J. Ge, Y. Zhang, C. Zhou, and J. Wei. Medical Imaging: Computer-Aided Diagnosis, volume 6915 of SPIE Proceedings, page 69152A. SPIE, (2008)

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Bladder cancer staging in CT urography: estimation and validation of decision thresholds for a radiomics-based decision support system.D. Gandikota, L. Hadjiiski, H. Chan, K. Cha, R. Samala, E. Caoili, R. Cohan, A. Weizer, A. Alva, C. Paramagul and 2 other author(s). Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 109500W. SPIE, (2019)Design and evaluation of a new automated method for the segmentation and characterization of masses on ultrasound images.J. Cui, B. Sahiner, H. Chan, A. Nees, C. Paramagul, L. Hadjiiski, C. Zhou, and J. Shi. Medical Imaging: Computer-Aided Diagnosis, volume 6915 of SPIE Proceedings, page 69150H. SPIE, (2008)Deep learning based bladder cancer treatment response assessment.E. Wu, L. Hadjiiski, R. Samala, H. Chan, K. Cha, C. Richter, R. Cohan, E. Caoili, C. Paramagul, A. Alva and 1 other author(s). Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 109503D. SPIE, (2019)Inter- and Intra-Observer Variability of Radiologists Evaluating CBIR Systems.L. Hadjiiski, H. chong Cho, H. Chan, B. Sahiner, M. Helvie, C. Paramagul, and A. Nees. Digital Mammography / IWDM, volume 7361 of Lecture Notes in Computer Science, page 482-489. Springer, (2012)Breast mass segmentation on dynamic contrast-enhanced magnetic resonance scans using the level set method.J. Shi, B. Sahiner, H. Chan, C. Paramagul, L. Hadjiiski, M. Helvie, Y. Wu, J. Ge, Y. Zhang, C. Zhou and 1 other author(s). Medical Imaging: Computer-Aided Diagnosis, volume 6915 of SPIE Proceedings, page 69152A. SPIE, (2008)Computer-Aided Characterization of Mammographic Masses: Accuracy of Mass Segmentation and Its Effect on Characterization.B. Sahiner, N. Petrick, H. Chan, L. Hadjiiski, C. Paramagul, M. Helvie, and M. Gurcan. IEEE Trans. Med. Imaging, 20 (12): 1275-1284 (2001)Homogenization of breast MRI across imaging centers and feature analysis using unsupervised deep embedding.R. Samala, H. Chan, L. Hadjiiski, C. Paramagul, M. Helvie, and C. Neal. Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 1095020. SPIE, (2019)ROC study: effects of computer-aided diagnosis on radiologists' characterization of malignant and benign breast masses in temporal pairs of mammograms.L. Hadjiiski, H. Chan, B. Sahiner, M. Helvie, M. Roubidoux, C. Blane, C. Paramagul, N. Petrick, J. Bailey, K. Klein and 5 other author(s). Medical Imaging: Image Processing, volume 5032 of SPIE Proceedings, SPIE, (2003)A computer-aided diagnosis system for prediction of the probability of malignancy of breast masses on ultrasound images.J. Cui, B. Sahiner, H. Chan, J. Shi, A. Nees, C. Paramagul, and L. Hadjiiski. Medical Imaging: Computer-Aided Diagnosis, volume 7260 of SPIE Proceedings, page 72600L. SPIE, (2009)A dynamic multiple thresholding method for automated breast boundary detection in digitized mammograms.Y. Wu, C. Zhou, L. Hadjiiski, J. Shi, J. Wei, C. Paramagul, B. Sahiner, and H. Chan. Medical Imaging: Image Processing, volume 6512 of SPIE Proceedings, page 65122U. SPIE, (2007)

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Breast mass segmentation on dynamic contrast-enhanced magnetic resonance scans using the level set method.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Breast mass segmentation on dynamic contrast-enhanced magnetic resonance scans using the level set method.

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Breast mass segmentation on dynamic contrast-enhanced magnetic resonance scans using the level set method.