東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Simulation and synthesis in medical ...

SASHIMI (Workshop) (2021 :)

FindBook

Google Book

Amazon

博客來

Simulation and synthesis in medical imaging = 6th International Workshop, SASHIMI 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Simulation and synthesis in medical imaging/ edited by David Svoboda ... [et al.].
其他題名:	6th International Workshop, SASHIMI 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
其他題名:	SASHIMI 2021
其他作者:	Svoboda, David.
團體作者:	SASHIMI (Workshop)
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	x, 154 p. :ill., digital ;24 cm.
內容註:	Method-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.
Contained By:	Springer Nature eBook
標題:	Diagnostic imaging - Congresses. - Digital techniques -
電子資源:	https://doi.org/10.1007/978-3-030-87592-3
ISBN:	9783030875923

Simulation and synthesis in medical imaging = 6th International Workshop, SASHIMI 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
Simulation and synthesis in medical imaging6th International Workshop, SASHIMI 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /[electronic resource] :SASHIMI 2021edited by David Svoboda ... [et al.]. - Cham :Springer International Publishing :2021. - x, 154 p. :ill., digital ;24 cm. - Lecture notes in computer science,129650302-9743 ;. - Lecture notes in computer science ;12965..

Method-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.

This 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.

ISBN: 9783030875923

Standard No.: 10.1007/978-3-030-87592-3doiSubjects--Topical Terms:

893046
Diagnostic imaging
--Digital techniques--Congresses.

LC Class. No.: RC78.7.D53 / S56 2021

Dewey Class. No.: 616.0754

Simulation and synthesis in medical imaging = 6th International Workshop, SASHIMI 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
LDR:03378nmm a2200385 a 4500 001 2251216
003 DE-He213
005 20210919203210.0
006 m d
007 cr nn 008maaau
008 220215s2021 sz s 0 eng d
020 $a 9783030875923 $q (electronic bk.)
020 $a 9783030875916 $q (paper)
024 7 $a 10.1007/978-3-030-87592-3 $2 doi
035 $a 978-3-030-87592-3
040 $a GP $c GP
041 0 $a eng
050 4 $a RC78.7.D53 $b S56 2021
072 7 $a UYT $2 bicssc
072 7 $a COM012000 $2 bisacsh
072 7 $a UYT $2 thema
072 7 $a UYQV $2 thema
082 0 4 $a 616.0754 $2 23
090 $a RC78.7.D53 $b S252 2021
111 2 $a SASHIMI (Workshop) $n (6th : $d 2021 : $c Online) $3 3517966
245 1 0 $a Simulation and synthesis in medical imaging $h [electronic resource] : $b 6th International Workshop, SASHIMI 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings / $c edited by David Svoboda ... [et al.].
246 3 $a SASHIMI 2021
246 3 $a MICCAI 2021
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a x, 154 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 12965
490 1 $a Image processing, computer vision, pattern recognition, and graphics
505 0 $a Method-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 $a This 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 $a Diagnostic imaging $x Digital techniques $v Congresses. $3 893046
650 0 $a Diagnostic imaging $x Data processing $v Congresses. $3 893542
650 1 4 $a Image Processing and Computer Vision. $3 891070
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Pattern Recognition. $3 891045
650 2 4 $a Computational Biology/Bioinformatics. $3 898313
700 1 $a Svoboda, David. $3 3453581
710 2 $a SpringerLink (Online service) $3 836513
711 2 $a International Conference on Medical Image Computing and Computer-Assisted Intervention $n (24th : $d 2021 : $c Online) $3 3517961
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science ; $v 12965. $3 3517967
830 0 $a Image processing, computer vision, pattern recognition, and graphics. $3 3382509
856 4 0 $u https://doi.org/10.1007/978-3-030-87592-3
950 $a Computer Science (SpringerNature-11645)