語系:
繁體中文
English
說明(常見問題)
圖資館首頁
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Simulation and synthesis in medical ...
~
(1998 :)
Simulation and synthesis in medical imagingthird International Workshop, SASHIMI 2018, held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018 : proceedings /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Simulation and synthesis in medical imagingedited by Ali Gooya ... [et al.].
其他題名:
third International Workshop, SASHIMI 2018, held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018 : proceedings /
其他題名:
SASHIMI 2018
其他作者:
Gooya, Ali.
團體作者:
出版者:
Cham :Springer International Publishing :2018.
面頁冊數:
x, 140 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
標題:
Diagnostic imagingCongresses.Digital techniques
電子資源:
https://doi.org/10.1007/978-3-030-00536-8
ISBN:
9783030005368$q(electronic bk.)
Simulation and synthesis in medical imagingthird International Workshop, SASHIMI 2018, held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018 : proceedings /
Simulation and synthesis in medical imaging
third International Workshop, SASHIMI 2018, held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018 : proceedings /[electronic resource] :SASHIMI 2018edited by Ali Gooya ... [et al.]. - Cham :Springer International Publishing :2018. - x, 140 p. :ill., digital ;24 cm. - Lecture notes in computer science,110370302-9743 ;. - Lecture notes in computer science ;4891..
Medical Image Synthesis for Data Augmentation and Anonymization Using Generative Adversarial Networks -- Data Augmentation Using synthetic Lesions Improves Machine Learning Detection of Microbleeds from MRI -- Deep Harmonization of Inconsistent MR Data for Consistent Volume Segmentation -- Cross-modality Image Synthesis from Unpaired Data Using CycleGAN: Effects of Gradient Consistency Loss and Training Data Size -- A Machine Learning Approach to Diffusion MRI Partial Volume Estimation -- Unsupervised Learning for Cross-domain Medical Image Synthesis Using Deformation Invariant Cycle Consistency Networks -- Deep Boosted Regression for MR TO CT Synthesis -- Model-Based Generation of Synthetic 3D Time-Lapse Sequences of Multiple Mutually Interacting Motile Cells with Filopodia -- MRI to FDG-PET: Cross-Modal Synthesis Using 3D U-Net for Multi-Modal Alzheimer's Classification -- Tubular Network Formation Process Using 3D Cellular Potts Model -- Deep Learning Based Coronary Artery Motion Artifact Compensation Using Style-Transfer Synthesis in CT Images -- Lung Nodule Synthesis Using CNN-based Latent Data Representation -- RS-Net: Regression-Segmentation 3D CNN for Synthesis of Full Resolution Missing Brain MRI in the Presence of Tumours -- Generating Magnetic Resonance Spectroscopy Imaging Data of Brain Tumours from Linear, Non-Linear and Deep Learning Models.
This book constitutes the refereed proceedings of the Third International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 14 full papers presented were carefully reviewed and selected from numerous submissions. This workshop continues to provide a state-of-the-art and integrative perspective on simulation and synthesis in medical imaging for the purpose of invigorating research and stimulating new ideas on how to build theoretical links, practical synergies, and best practices between these two research directions.
ISBN: 9783030005368$q(electronic bk.)
Standard No.: 10.1007/978-3-030-00536-8doiSubjects--Topical Terms:
445235
Diagnostic imaging
--Digital techniques--Congresses.
LC Class. No.: TA1634
Dewey Class. No.: 006.6
Simulation and synthesis in medical imagingthird International Workshop, SASHIMI 2018, held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018 : proceedings /
LDR
:03324nmm a2200385 a 4500
001
544523
003
DE-He213
005
20180913021408.0
006
m d
007
cr nn 008maaau
008
190508s2018 sz s 0 eng d
020
$a
9783030005368$q(electronic bk.)
020
$a
9783030005351$q(paper)
024
7
$a
10.1007/978-3-030-00536-8
$2
doi
035
$a
978-3-030-00536-8
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
TA1634
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
006.6
$2
23
090
$a
TA1634
$b
.S252 2018
111
2
$n
(3rd :
$d
1998 :
$c
Amsterdam, Netherlands)
$3
194767
245
1 0
$a
Simulation and synthesis in medical imaging
$h
[electronic resource] :
$b
third International Workshop, SASHIMI 2018, held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018 : proceedings /
$c
edited by Ali Gooya ... [et al.].
246
3
$a
SASHIMI 2018
246
3
$a
MICCAI 2018
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2018.
300
$a
x, 140 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Lecture notes in computer science,
$x
0302-9743 ;
$v
11037
490
1
$a
Image processing, computer vision, pattern recognition, and graphics
505
0
$a
Medical Image Synthesis for Data Augmentation and Anonymization Using Generative Adversarial Networks -- Data Augmentation Using synthetic Lesions Improves Machine Learning Detection of Microbleeds from MRI -- Deep Harmonization of Inconsistent MR Data for Consistent Volume Segmentation -- Cross-modality Image Synthesis from Unpaired Data Using CycleGAN: Effects of Gradient Consistency Loss and Training Data Size -- A Machine Learning Approach to Diffusion MRI Partial Volume Estimation -- Unsupervised Learning for Cross-domain Medical Image Synthesis Using Deformation Invariant Cycle Consistency Networks -- Deep Boosted Regression for MR TO CT Synthesis -- Model-Based Generation of Synthetic 3D Time-Lapse Sequences of Multiple Mutually Interacting Motile Cells with Filopodia -- MRI to FDG-PET: Cross-Modal Synthesis Using 3D U-Net for Multi-Modal Alzheimer's Classification -- Tubular Network Formation Process Using 3D Cellular Potts Model -- Deep Learning Based Coronary Artery Motion Artifact Compensation Using Style-Transfer Synthesis in CT Images -- Lung Nodule Synthesis Using CNN-based Latent Data Representation -- RS-Net: Regression-Segmentation 3D CNN for Synthesis of Full Resolution Missing Brain MRI in the Presence of Tumours -- Generating Magnetic Resonance Spectroscopy Imaging Data of Brain Tumours from Linear, Non-Linear and Deep Learning Models.
520
$a
This book constitutes the refereed proceedings of the Third International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 14 full papers presented were carefully reviewed and selected from numerous submissions. This workshop continues to provide a state-of-the-art and integrative perspective on simulation and synthesis in medical imaging for the purpose of invigorating research and stimulating new ideas on how to build theoretical links, practical synergies, and best practices between these two research directions.
650
0
$a
Diagnostic imaging
$x
Digital techniques
$v
Congresses.
$3
445235
650
0
$a
Diagnostic imaging
$x
Data processing
$v
Congresses.
$3
445765
650
1 4
$a
Image Processing and Computer Vision.
$3
274051
650
2 4
$a
Health Informatics.
$3
274212
650
2 4
$a
Artificial Intelligence (incl. Robotics)
$3
252959
650
2 4
$a
Systems and Data Security.
$3
274481
700
1
$a
Gooya, Ali.
$3
823082
710
2
$a
SpringerLink (Online service)
$3
273601
711
2
$n
(3rd :
$d
1998 :
$c
Amsterdam, Netherlands)
$3
194767
773
0
$t
Springer eBooks
830
0
$a
Lecture notes in computer science ;
$v
4891.
$3
383229
830
0
$a
Image processing, computer vision, pattern recognition, and graphics.
$3
823073
856
4 0
$u
https://doi.org/10.1007/978-3-030-00536-8
950
$a
Computer Science (Springer-11645)
筆 0 讀者評論
全部
電子館藏
館藏
1 筆 • 頁數 1 •
1
條碼號
館藏地
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
000000161967
電子館藏
1圖書
電子書
EB TA1634 .S252 2018 2018
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
多媒體檔案
https://doi.org/10.1007/978-3-030-00536-8
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼
登入