國立高雄大學圖資館 |

Language: English

Back

Graph learning in medical imagingfir...

(1998 :)

Graph learning in medical imagingfirst International Workshop, GLMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Graph learning in medical imagingedited by Daoqiang Zhang ... [et al.].
Reminder of title:	first International Workshop, GLMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019 : proceedings /
remainder title:	GLMI 2019
other author:	Zhang, Daoqiang.
corporate name:
Published:	Cham :Springer International Publishing :2019.
Description:	ix, 182 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Diagnostic imagingCongresses.Digital techniques
Online resource:	https://doi.org/10.1007/978-3-030-35817-4
ISBN:	9783030358174$q(electronic bk.)

Graph learning in medical imagingfirst International Workshop, GLMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019 : proceedings /
Graph learning in medical imagingfirst International Workshop, GLMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019 : proceedings /[electronic resource] :GLMI 2019edited by Daoqiang Zhang ... [et al.]. - Cham :Springer International Publishing :2019. - ix, 182 p. :ill., digital ;24 cm. - Lecture notes in computer science,118490302-9743 ;. - Lecture notes in computer science ;4891..

Graph Hyperalignment for Multi-Subject fMRI Functional Alignment -- Interactive 3D Segmentation Editing and Refinement via Gated Graph Neural Networks -- Adaptive Thresholding of Functional Connectivity Networks for fMRI-based Brain Disease Analysis -- Graph-kernel-based Multi-task Structured Feature Selection on Multi-level Functional Connectivity Networks for Brain Disease Classification -- Linking convolutional neural networks with graph convolutional networks: application in pulmonary artery-vein separation -- Comparative Analysis of Magnetic Resonance Fingerprinting Dictionaries via Dimensionality Reduction -- Learning Deformable Point Set Registration with Regularized Dynamic Graph CNNs for Large Lung Motion in COPD Patients -- Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography -- Triplet Graph Convolutional Network forMulti-scale Analysis of Functional Connectivityusing Functional MRI -- Multi-Scale Graph Convolutional Network for Mild Cognitive Impairment Detection -- DeepBundle: Fiber Bundle Parcellation With Graph CNNs -- Identification of Functional Connectivity Features in Depression Subtypes Using a Data-Driven Approach -- Movie-watching fMRI Reveals Inter-subject Synchrony Alteration in Functional Brain Activity in ADHD -- Weakly- and Semi- Supervised Graph CNN for identifying Basal Cell Carcinoma on Pathological images -- Geometric Brain Surface Network For Brain Cortical Parcellation -- Automatic Detection of Craniomaxillofacial Anatomical Landmarks on CBCT Images using 3D Mask R-CNN -- Discriminative-Region-Aware Residual Network for Adolescent Brain Structure and Cognitive Development Analysis -- Graph Modeling for Identifying Breast Tumor Located in Dense Background of a Mammogram -- OCD Diagnosis via Smoothing Sparse Network and Stacked Sparse Auto-Encoder Learning -- A Longitudinal MRI Study of Amygdala and Hippocampal Subfields for Infants with Risk of Autism -- CNS: CycleGAN-assisted Neonatal Segmentation Model for Cross-Datasets.

This book constitutes the refereed proceedings of the First International Workshop on Graph Learning in Medical Imaging, GLMI 2019, held in conjunction with MICCAI 2019 in Shenzhen, China, in October 2019. The 21 full papers presented were carefully reviewed and selected from 42 submissions. The papers focus on major trends and challenges of graph learning in medical imaging and present original work aimed to identify new cutting-edge techniques and their applications in medical imaging.

ISBN: 9783030358174$q(electronic bk.)

Standard No.: 10.1007/978-3-030-35817-4doiSubjects--Topical Terms:

445235
Diagnostic imaging
--Digital techniques--Congresses.

LC Class. No.: RC78.7.D53 / G55 2019

Dewey Class. No.: 616.0754

Graph learning in medical imagingfirst International Workshop, GLMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019 : proceedings /
LDR:03821nmm a2200373 a 4500 001 569414
003 DE-He213
005 20191113161715.0
006 m d
007 cr nn 008maaau
008 200723s2019 gw s 0 eng d
020 $a 9783030358174$q(electronic bk.)
020 $a 9783030358167$q(paper)
024 7 $a 10.1007/978-3-030-35817-4 $2 doi
035 $a 978-3-030-35817-4
040 $a GP $c GP
041 0 $a eng
050 4 $a RC78.7.D53 $b G55 2019
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 616.0754 $2 23
090 $a RC78.7.D53 $b G561 2019
111 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
245 1 0 $a Graph learning in medical imaging $h [electronic resource] : $b first International Workshop, GLMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019 : proceedings / $c edited by Daoqiang Zhang ... [et al.].
246 3 $a GLMI 2019
246 3 $a MICCAI 2019
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a ix, 182 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 11849
490 1 $a Image processing, computer vision, pattern recognition, and graphics
505 0 $a Graph Hyperalignment for Multi-Subject fMRI Functional Alignment -- Interactive 3D Segmentation Editing and Refinement via Gated Graph Neural Networks -- Adaptive Thresholding of Functional Connectivity Networks for fMRI-based Brain Disease Analysis -- Graph-kernel-based Multi-task Structured Feature Selection on Multi-level Functional Connectivity Networks for Brain Disease Classification -- Linking convolutional neural networks with graph convolutional networks: application in pulmonary artery-vein separation -- Comparative Analysis of Magnetic Resonance Fingerprinting Dictionaries via Dimensionality Reduction -- Learning Deformable Point Set Registration with Regularized Dynamic Graph CNNs for Large Lung Motion in COPD Patients -- Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography -- Triplet Graph Convolutional Network forMulti-scale Analysis of Functional Connectivityusing Functional MRI -- Multi-Scale Graph Convolutional Network for Mild Cognitive Impairment Detection -- DeepBundle: Fiber Bundle Parcellation With Graph CNNs -- Identification of Functional Connectivity Features in Depression Subtypes Using a Data-Driven Approach -- Movie-watching fMRI Reveals Inter-subject Synchrony Alteration in Functional Brain Activity in ADHD -- Weakly- and Semi- Supervised Graph CNN for identifying Basal Cell Carcinoma on Pathological images -- Geometric Brain Surface Network For Brain Cortical Parcellation -- Automatic Detection of Craniomaxillofacial Anatomical Landmarks on CBCT Images using 3D Mask R-CNN -- Discriminative-Region-Aware Residual Network for Adolescent Brain Structure and Cognitive Development Analysis -- Graph Modeling for Identifying Breast Tumor Located in Dense Background of a Mammogram -- OCD Diagnosis via Smoothing Sparse Network and Stacked Sparse Auto-Encoder Learning -- A Longitudinal MRI Study of Amygdala and Hippocampal Subfields for Infants with Risk of Autism -- CNS: CycleGAN-assisted Neonatal Segmentation Model for Cross-Datasets.
520 $a This book constitutes the refereed proceedings of the First International Workshop on Graph Learning in Medical Imaging, GLMI 2019, held in conjunction with MICCAI 2019 in Shenzhen, China, in October 2019. The 21 full papers presented were carefully reviewed and selected from 42 submissions. The papers focus on major trends and challenges of graph learning in medical imaging and present original work aimed to identify new cutting-edge techniques and their applications in medical imaging.
650 0 $a Diagnostic imaging $x Digital techniques $v Congresses. $3 445235
650 1 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Image Processing and Computer Vision. $3 274051
650 2 4 $a Pattern Recognition. $3 273706
650 2 4 $a Computer Appl. in Social and Behavioral Sciences. $3 274376
700 1 $a Zhang, Daoqiang. $3 700043
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/10.1007/978-3-030-35817-4
950 $a Computer Science (Springer-11645)