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Efficient Hilbert transform-based alternative to Tofts physiological models for representing MRI dynamic contrast-enhanced images in computer-aided diagnosis of prostate cancer.

K. Boehm, S. Wang, K. Burtt, B. Turkbey, S. Weisenthal, P. Pinto, P. Choyke, B. Wood, N. Petrick, B. Sahiner, and R. Summers. Medical Imaging: Computer-Aided Diagnosis, volume 9414 of SPIE Proceedings, page 94140S. SPIE, (2015)

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Baris Yanik

Baris Ünver

Caroline Barisch

Baris Serifsoy

Imam Baris

Other publications of authors with the same name

Deeply-Supervised CNN for Prostate Segmentation.Q. Zhu, B. Du, B. Turkbey, P. Choyke, and P. Yan. CoRR, (2017)Realtime TRUS/MRI Fusion Targeted-Biopsy for Prostate Cancer: A Clinical Demonstration of Increased Positive Biopsy Rates.S. Kadoury, P. Yan, S. Xu, N. Glossop, P. Choyke, B. Turkbey, P. Pinto, B. Wood, and J. Kruecker. Prostate Cancer Imaging, volume 6367 of Lecture Notes in Computer Science, page 52-62. Springer, (2010)Exploiting Interslice Correlation for MRI Prostate Image Segmentation, from Recursive Neural Networks Aspect.Q. Zhu, B. Du, B. Turkbey, P. Choyke, and P. Yan. Complex., (2018)Discrete Deformable Model Guided by Partial Active Shape Model for TRUS Image Segmentation.P. Yan, S. Xu, B. Turkbey, and J. Kruecker. IEEE Trans. Biomed. Eng., 57 (5): 1158-1166 (2010)Active appearance model and deep learning for more accurate prostate segmentation on MRI.R. Cheng, H. Roth, L. Lu, S. Wang, B. Turkbey, W. Gandler, E. McCreedy, H. Agarwal, P. Choyke, R. Summers and 1 other author(s). Medical Imaging: Image Processing, volume 9784 of SPIE Proceedings, page 97842I. SPIE, (2016)Atlas based AAM and SVM model for fully automatic MRI prostate segmentation.R. Cheng, B. Turkbey, W. Gandler, H. Agarwal, V. Shah, A. Bokinsky, E. McCreedy, S. Wang, S. Sankineni, M. Bernardo and 3 other author(s). EMBC, page 2881-2585. IEEE, (2014)A collaborative computer aided diagnosis (C-CAD) system with eye-tracking, sparse attentional model, and deep learning.N. Khosravan, H. Celik, B. Turkbey, E. Jones, B. Wood, and U. Bagci. Medical Image Anal., (2019)Using YOLO v7 to Detect Kidney in Magnetic Resonance Imaging.P. Anari, F. Obiezu, N. Lay, F. Firouzabadi, A. Chaurasia, M. Golagha, S. Singh, F. Homayounieh, A. Zahergivar, S. Harmon and 9 other author(s). CoRR, (2024)Multi-Task Learning for Registering Images With Large Deformation.B. Du, J. Liao, B. Turkbey, and P. Yan. IEEE J. Biomed. Health Informatics, 25 (5): 1624-1633 (2021)Global structure constrained local shape prior estimation for medical image segmentation.P. Yan, W. Zhang, B. Turkbey, P. Choyke, and X. Li. Comput. Vis. Image Underst., 117 (9): 1017-1026 (2013)

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