LEADER 04269nam 22006495 450 001 9910502631703321 005 20251107152703.0 010 $a3-030-87592-X 024 7 $a10.1007/978-3-030-87592-3 035 $a(CKB)4940000000612716 035 $a(MiAaPQ)EBC6730649 035 $a(Au-PeEL)EBL6730649 035 $a(OCoLC)1268984750 035 $a(PPN)258051914 035 $a(DE-He213)978-3-030-87592-3 035 $a(EXLCZ)994940000000612716 100 $a20210919d2021 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSimulation and Synthesis in Medical Imaging $e6th International Workshop, SASHIMI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings /$fedited by David Svoboda, Ninon Burgos, Jelmer M. Wolterink, Can Zhao 205 $a1st ed. 2021. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (162 pages) 225 1 $aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v12965 300 $aIncludes index. 311 08$a3-030-87591-1 327 $aMethod-Oriented Papers -- Detail matters: high-frequency content for realistic synthetic brain MRI generation -- Joint Image and Label Self-Super-Resolution -- Super-resolution by Latent Space Exploration: Training with Poorly-aligned Clinical and Micro CT Image Dataset -- A Glimpse into the Future: Disease Progression Simulation for Breast Cancer in Mammograms -- Synth-by-Reg (SbR): Contrastive learning for synthesis-based registration of paired images -- Learning-based Template Synthesis For Groupwise Image Registration -- The role of MRI physics in brain segmentation CNNs: achieving acquisition invariance and instructive uncertainties -- Transfer Learning in Optical Microscopy -- X-ray synthesis based on triangular mesh models using GPU-accelerated ray tracing for multi-modal breast image registration -- Application-Oriented Papers -- Frozen-to-Paraffin: Categorization of Histological Frozen Sections by the Aid of Paraffin Sections and Generative Adversarial Networks -- SequenceGAN: Generating Fundus Fluorescence Angiography Sequences from Structure Fundus Image -- Cerebral Blood Volume Prediction based on Multi-modality Magnetic Resonance Imaging -- Cine-MRI simulation to evaluate tumor tracking -- GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models. 330 $aThis book constitutes the refereed proceedings of the 6th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in September 2021.* The 14 full papers presented were carefully reviewed and selected from 18 submissions. The contributions span the following broad categories in alignment with the initial call-for-papers: methods based on generative models or adversarial learning for MRI/CT/ microscopy image synthesis, and several applications of image synthesis and simulation for data augmentation, image enhancement, or segmentation. *The workshop was held virtually. 410 0$aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v12965 606 $aComputer vision 606 $aArtificial intelligence 606 $aPattern recognition systems 606 $aBioinformatics 606 $aComputer Vision 606 $aArtificial Intelligence 606 $aAutomated Pattern Recognition 606 $aComputational and Systems Biology 615 0$aComputer vision. 615 0$aArtificial intelligence. 615 0$aPattern recognition systems. 615 0$aBioinformatics. 615 14$aComputer Vision. 615 24$aArtificial Intelligence. 615 24$aAutomated Pattern Recognition. 615 24$aComputational and Systems Biology. 676 $a616.0754 702 $aSvoboda$b David 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910502631703321 996 $aSimulation and Synthesis in Medical Imaging$92916762 997 $aUNINA