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245 1 0 _aSimulation and Synthesis in Medical Imaging
_h[electronic resource] :
_b6th International Workshop, SASHIMI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings /
_cedited by David Svoboda, Ninon Burgos, Jelmer M. Wolterink, Can Zhao.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aX, 154 p. 58 illus., 47 illus. in color.
_bonline resource.
336 _atext
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490 1 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
_v12965
505 0 _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.
520 _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.
650 0 _aComputer vision.
_9119530
650 0 _aArtificial intelligence.
_93407
650 0 _aPattern recognition systems.
_93953
650 0 _aBioinformatics.
_99561
650 1 4 _aComputer Vision.
_9119531
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aAutomated Pattern Recognition.
_931568
650 2 4 _aComputational and Systems Biology.
_931619
700 1 _aSvoboda, David.
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700 1 _aBurgos, Ninon.
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700 1 _aWolterink, Jelmer M.
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700 1 _aZhao, Can.
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710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
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_9119537
856 4 0 _uhttps://doi.org/10.1007/978-3-030-87592-3
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