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Mixture Modeling of Global Shape Priors and Autoencoding Local Intensity Priors for Left Atrium Segmentation., , , , , and . CoRR, (2019)From Label Maps to Generative Shape Models: A Variational Bayesian Learning Approach., and . IPMI, volume 10265 of Lecture Notes in Computer Science, page 93-105. Springer, (2017)Towards a Statistical Shape-Aware Deformable Contour Model for Cranial Nerve Identification., , , , , , , and . CLIP@MICCAI, volume 9958 of Lecture Notes in Computer Science, page 68-76. (2016)Helmholtz HSH-Based Basis: A Compact Phenomenological Representation of Arbitrary Reflectance., and . Informatica, 26 (4): 593-620 (2015)Two-Stage Deep Learning Framework for Quality Assessment of Left Atrial Late Gadolinium Enhanced MRI Images., , , , , , , , and . CoRR, (2023)Visualization of topology optimization designs with representative subset selection., , , , , and . CoRR, (2020)Towards Efficient and Compact Phenomenological Representation of Arbitrary Bidirectional Surface Reflectance., , and . BMVC, page 1-11. BMVA Press, (2011)Mixture Modeling of Global Shape Priors and Autoencoding Local Intensity Priors for Left Atrium Segmentation., , , , , and . STACOM@MICCAI, volume 11395 of Lecture Notes in Computer Science, page 357-367. Springer, (2018)Efficient Segmentation Pipeline Using Diffeomorphic Image Registration: A Validation Study., , , , , , , , and . CinC, page 1-4. IEEE, (2019)ShapeOdds: Variational Bayesian Learning of Generative Shape Models., and . CVPR, page 2185-2196. IEEE Computer Society, (2017)