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ORCID5th SASHIMI@MICCAI 2020: Lima, Peru
- Ninon Burgos
, David Svoboda, Jelmer M. Wolterink, Can Zhao:
Simulation and Synthesis in Medical Imaging - 5th International Workshop, SASHIMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings. Lecture Notes in Computer Science 12417, Springer 2020, ISBN 978-3-030-59519-7 - Dzung L. Pham, Yi-Yu Chou, Blake E. Dewey, Daniel S. Reich, John A. Butman, Snehashis Roy:
Contrast Adaptive Tissue Classification by Alternating Segmentation and Synthesis. 1-10 - Filip Rusak, Rodrigo Santa Cruz, Pierrick Bourgeat, Clinton Fookes, Jurgen Fripp, Andrew P. Bradley, Olivier Salvado:
3D Brain MRI GAN-Based Synthesis Conditioned on Partial Volume Maps. 11-20 - Lianrui Zuo, Blake E. Dewey, Aaron Carass, Yufan He, Muhan Shao, Jacob C. Reinhold, Jerry L. Prince:
Synthesizing Realistic Brain MR Images with Noise Control. 21-31 - Pamela R. Jackson, Andrea Hawkins-Daarud, Kristin R. Swanson:
Simulated Diffusion Weighted Images Based on Model-Predicted Tumor Growth. 32-40 - José V. Manjón, José E. Romero, Roberto Vivó Hernando, Gregorio Rubio, Fernando Aparici-Robles, María de la Iglesia-Vayá, Thomas Tourdias, Pierrick Coupé:
Blind MRI Brain Lesion Inpainting Using Deep Learning. 41-49 - Hongyu Wang, Jun Feng, Xiaoying Pan, Di Yang, Bao-ying Chen:
High-Quality Interpolation of Breast DCE-MRI Using Learned Transformations. 50-59 - Reuben R. Shamir, Ze'ev Bomzon:
A Method for Tumor Treating Fields Fast Estimation. 60-67 - Yasmina Al Khalil, Sina Amirrajab, Cristian Lorenz, Jürgen Weese, Marcel Breeuwer:
Heterogeneous Virtual Population of Simulated CMR Images for Improving the Generalization of Cardiac Segmentation Algorithms. 68-79 - Jingya Liu, Yingli Tian, A. Muhtesem Agildere, K. Murat Haberal, Mehmet Coskun, Cihan Duzgol, Oguz Akin:
DyeFreeNet: Deep Virtual Contrast CT Synthesis. 80-89 - Nicolas H. Nbonsou Tegang, Jean-Rassaire Fouefack, Bhushan Borotikar, Valérie Burdin, Tania S. Douglas, Tinashe E. M. Mutsvangwa:
A Gaussian Process Model Based Generative Framework for Data Augmentation of Multi-modal 3D Image Volumes. 90-100 - Zi Lin, Manli Zhong, Xiangzhu Zeng, Chuyang Ye:
Frequency-Selective Learning for CT to MR Synthesis. 101-109 - Kerstin Kläser, Pedro Borges, Richard Shaw, Marta Ranzini, Marc Modat, David Atkinson, Kris Thielemans, Brian F. Hutton, Vicky Goh, Gary J. Cook, M. Jorge Cardoso, Sébastien Ourselin:
Uncertainty-Aware Multi-resolution Whole-Body MR to CT Synthesis. 110-119 - María Escobar, Angela Castillo, Andrés Romero, Pablo Arbeláez:
UltraGAN: Ultrasound Enhancement Through Adversarial Generation. 120-130 - Georg Wimmer, Michael Gadermayr, Andreas Vécsei, Andreas Uhl:
Improving Endoscopic Decision Support Systems by Translating Between Imaging Modalities. 131-141 - Wanyue Li, Yi He, Jing Wang, Wen Kong, Yiwei Chen, Guohua Shi:
An Unsupervised Adversarial Learning Approach to Fundus Fluorescein Angiography Image Synthesis for Leakage Detection. 142-152 - Manuel Traub, Johannes Stegmaier:
Towards Automatic Embryo Staging in 3D+t Microscopy Images Using Convolutional Neural Networks and PointNets. 153-163 - Srijay Deshpande, Fayyaz A. Minhas, Nasir M. Rajpoot:
Train Small, Generate Big: Synthesis of Colorectal Cancer Histology Images. 164-173 - Dejan Stepec, Danijel Skocaj:
Image Synthesis as a Pretext for Unsupervised Histopathological Diagnosis. 174-183 - Ziteng Liu, Ahmet Çakir, Jack H. Noble:
Auditory Nerve Fiber Health Estimation Using Patient Specific Cochlear Implant Stimulation Models. 184-194
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