Abstract is missing.
- Detail Matters: High-Frequency Content for Realistic Synthetic MRI GenerationFilip Rusak, Rodrigo Santa Cruz, Elliot Smith, Jurgen Fripp, Clinton Fookes, Pierrick Bourgeat, Andrew P. Bradley. 3-13 [doi]
- Joint Image and Label Self-super-ResolutionSamuel W. Remedios, Shuo Han, Blake E. Dewey, Dzung L. Pham, Jerry L. Prince, Aaron Carass. 14-23 [doi]
- Super-Resolution by Latent Space Exploration: Training with Poorly-Aligned Clinical and Micro CT Image DatasetTong Zheng, Hirohisa Oda, Yuichiro Hayashi, Shota Nakamura, Masahiro Oda, Kensaku Mori. 24-33 [doi]
- A Glimpse into the Future: Disease Progression Simulation for Breast Cancer in MammogramsIbrahim Jubran, Moshiko Raboh, Shaked Perek, David Gruen, Efrat Hexter. 34-43 [doi]
- Synth-by-Reg (SbR): Contrastive Learning for Synthesis-Based Registration of Paired ImagesAdrià Casamitjana, Matteo Mancini, Juan Eugenio Iglesias. 44-54 [doi]
- Learning-Based Template Synthesis for Groupwise Image RegistrationZiyi He, Albert C. S. Chung. 55-66 [doi]
- The Role of MRI Physics in Brain Segmentation CNNs: Achieving Acquisition Invariance and Instructive UncertaintiesPedro Borges, Richard Shaw, Thomas Varsavsky, Kerstin Kläser, David Thomas 0002, Ivana Drobnjak, Sébastien Ourselin, Manuel Jorge Cardoso. 67-76 [doi]
- Transfer Learning in Optical MicroscopyMarián Kozlovský, David Wiesner, David Svoboda. 77-86 [doi]
- X-ray Synthesis Based on Triangular Mesh Models Using GPU-Accelerated Ray Tracing for Multi-modal Breast Image RegistrationJ. Maul, S. Said, Nicole V. Ruiter, Torsten Hopp. 87-96 [doi]
- Frozen-to-Paraffin: Categorization of Histological Frozen Sections by the Aid of Paraffin Sections and Generative Adversarial NetworksMichael Gadermayr, Maximilian Ernst Tschuchnig, Lea Maria Stangassinger, Christina Kreutzer, Sebastien Couillard-Despres, Gertie Janneke Oostingh, Anton Hittmair. 99-109 [doi]
- SequenceGAN: Generating Fundus Fluorescence Angiography Sequences from Structure Fundus ImageWanyue Li, Yi He 0006, Wen Kong, Jing Wang, Guohua Deng, Yiwei Chen, Guohua Shi. 110-120 [doi]
- Cerebral Blood Volume Prediction Based on Multi-modality Magnetic Resonance ImagingYongsheng Pan, Jingyu Huang, Bao Wang, Peng Zhao, Yingchao Liu, Yong Xia. 121-130 [doi]
- Cine-MRI Simulation to Evaluate Tumor TrackingJosé D. Tascón-Vidarte, Isak Wahlstedt, Julien Jomier, Kenny Erleben, Ivan R. Vogelius, Sune Darkner. 131-141 [doi]
- GAN-Based Synthetic FDG PET Images from T1 Brain MRI Can Serve to Improve Performance of Deep Unsupervised Anomaly Detection ModelsDaria Zotova, Julien Jung, Carole Lartizien. 142-152 [doi]