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Simulation and Synthesis in Medical Imaging: 8th International Workshop, SASHIMI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings 1st ed. 2023 [Pehme köide]

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  • Formaat: Paperback / softback, 142 pages, kõrgus x laius: 235x155 mm, kaal: 242 g, 39 Illustrations, color; 16 Illustrations, black and white; VIII, 142 p. 55 illus., 39 illus. in color., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 14288
  • Ilmumisaeg: 07-Oct-2023
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031446887
  • ISBN-13: 9783031446887
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Simulation and Synthesis in Medical Imaging: 8th International Workshop, SASHIMI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings 1st ed. 2023Suurem pilt
  • Formaat: Paperback / softback, 142 pages, kõrgus x laius: 235x155 mm, kaal: 242 g, 39 Illustrations, color; 16 Illustrations, black and white; VIII, 142 p. 55 illus., 39 illus. in color., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 14288
  • Ilmumisaeg: 07-Oct-2023
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031446887
  • ISBN-13: 9783031446887
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783031446887.html
Märksõnad:

This book constitutes the refereed proceedings of the 8th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2023, held in conjunction with MICCAI 2023, in Vancouver, Canada, in October 2023.

The 13 full papers included in this book were carefully reviewed and selected from 16 submissions. They span a wide range of topics relevant to SASHIMI, and reflect recent developments in methods for segmentation, image-to-image translation, super-resolution, and image synthesis. Applications include MRI imaging, echocardiography, PET, and digital pathology.


Transformers for CT Reconstruction From Monoplanar and Biplanar
Radiographs Super-resolution Segmentation network for inner-ear
tissue segmentation.-      Multi-Phase Liver-Specific DCE-MRI Translation
via a Registration-Guided GAN.- Learned Local Attention Maps for
Synthesising Vessel Segmentations from T2 MRI Physics-Aware Motion
Simulation for T2*-Weighted Brain MRI.- Unsupervised heteromodal
physics-informed representation of MRI data: tackling data harmonisation,
imputation and domain shift.- TAI-GAN: Temporally and Anatomically Informed
GAN for early-to-late frame conversion in dynamic cardiac PET motion
correction.-  How Good Are Synthetic Medical Images? An Empirical Study
with Lung Ultrasound Unsupervised Liver Tumor Segmentation with
Pseudo Anomaly Synthesis.-       Improving style transfer in dynamic
contrast enhanced MRI using a spatio-temporal approach Synthetic
Singleplex-Image Generation in Multiplex-Brightfield Immunohistochemistry.-
Digital Pathology using Deep Generative Models Self-Supervised
Super-Resolution for Anisotropic MR Images with and without Slice Gap
DIFF·3: A latent diffusion model for the generation of synthetic 3D
echocardiographic images and corresponding labels.