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Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge.

C. Martín-Isla, V. Campello, C. Izquierdo, K. Kushibar, C. Sendra-Balcells, P. Gkontra, A. Sojoudi, M. Fulton, T. Arega, K. Punithakumar, L. Li, X. Sun, Y. Khalil, D. Liu, S. Jabbar, S. Queiros, F. Galati, M. Mazher, Z. Gao, M. Beetz, L. Tautz, C. Galazis, M. Varela, M. Hüllebrand, V. Grau, X. Zhuang, D. Puig, M. Zuluaga, H. ud Din, D. Metaxas, M. Breeuwer, R. van der Geest, M. Noga, S. Bricq, M. Rentschler, A. Guala, S. Petersen, S. Escalera, J. Palomares, and K. Lekadir. IEEE J. Biomed. Health Informatics, 27 (7): 3302-3313 (July 2023)

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Left ventricle segmentation in MRI via convex relaxed distribution matching.C. Nambakhsh, J. Yuan, K. Punithakumar, A. Goela, M. Rajchl, T. Peters, and I. Ayed. Medical Image Anal., 17 (8): 1010-1024 (2013)Max-flow segmentation of the left ventricle by recovering subject-specific distributions via a bound of the Bhattacharyya measure.I. Ayed, H. mei Chen, K. Punithakumar, I. Ross, and S. Li. Medical Image Anal., 16 (1): 87-100 (2012)Distributed Tracking with a PHD Filter using Efficient Measurement Encoding.B. Habtemariam, A. Aravinthan, R. Tharmarasa, K. Punithakumar, T. Lang, and T. Kirubarajan. J. Adv. Inf. Fusion, 7 (2): 114-130 (2012)A GPU-Accelerated Deformable Image Registration Algorithm With Applications to Right Ventricular Segmentation.K. Punithakumar, P. Boulanger, and M. Noga. IEEE Access, (2017)Tracking tumor boundary using point correspondence for adaptive radio therapy.N. Tahmasebi, P. Boulanger, J. Yun, B. Fallone, and K. Punithakumar. Comput. Methods Programs Biomed., (2018)Multitarget Tracking using Probability Hypothesis Density Smoothing.N. Nadarajah, T. Kirubarajan, T. Lang, M. McDonald, and K. Punithakumar. IEEE Trans. Aerosp. Electron. Syst., 47 (4): 2344-2360 (2011)Assessment of Regional Myocardial Function via Statistical Features in MR Images.M. Afshin, I. Ayed, K. Punithakumar, M. Law, A. Islam, A. Goela, I. Ross, T. Peters, and S. Li. MICCAI (3), volume 6893 of Lecture Notes in Computer Science, page 107-114. Springer, (2011)Unsupervised diffeomorphic cardiac image registration using parameterization of the deformation field.A. Sheikhjafari, D. Krishnaswamy, M. Noga, N. Ray, and K. Punithakumar. CoRR, (2022)Automated Segmentation of the Right Ventricle from Magnetic Resonance Imaging Using Deep Convolutional Neural Networks.K. Punithakumar, A. Carscadden, and M. Noga. STACOM@MICCAI, volume 13131 of Lecture Notes in Computer Science, page 344-351. Springer, (2021)Graph Cuts-based Segmentation of Alveolar Bone in Ultrasound Imaging.K. Nguyen, D. Shi, N. Kaipatur, E. Lou, P. Major, K. Punithakumar, and L. Le. BIBM, page 2049-2055. IEEE Computer Society, (2018)

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Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge.

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Disambiguation of "Punithakumar, Kumaradevan"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge.

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Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge.