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

Machine learning in clinical neuroim...

MLCN (Workshop) (2021 :)

FindBook

Google Book

Amazon

博客來

Machine learning in clinical neuroimaging = 4th International Workshop, MLCN 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:	Machine learning in clinical neuroimaging/ edited by Ahmed Abdulkadir ... [et al.].
其他題名:	4th International Workshop, MLCN 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
其他題名:	MLCN 2021
其他作者:	Abdulkadir, Ahmed.
團體作者:	MLCN (Workshop)
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	xi, 176 p. :ill., digital ;24 cm.
內容註:	Computational Anatomy -- Unfolding the medial temporal lobe cortex to characterize neurodegeneration due to Alzheimer's disease pathology using ex vivo imaging -- Distinguishing Healthy Ageing from Dementia: a Biomechanical Simulation of Brain Atrophy using Deep Networks -- Towards Self-Explainable Classifiers and Regressors in Neuroimaging with Normalizing Flows -- Patch vs. global image-based unsupervised anomaly detection in MR brain scans of early Parkinsonian patients -- MRI image registration considerably improves CNN-based disease classification -- Dynamic Sub-graph Learning for Patch-based Cortical Folding Classification -- Detection of abnormal folding patterns with unsupervised deep generative models -- PialNN: A Fast Deep Learning Framework for Cortical Pial Surface Reconstruction -- Multi-Modal Brain Segmentation Using Hyper-Fused Convolutional Neural Network -- Robust Hydrocephalus Brain Segmentation via Globally and Locally Spatial Guidance -- Brain Networks and Time Series -- Geometric Deep Learning of the Human Connectome Project Multimodal Cortical Parcellation -- Deep Stacking Networks for Conditional Nonlinear Granger Causal Modeling of fMRI Data -- Dynamic Adaptive Spatio-temporal Graph Convolution for fMRI Modelling -- Structure-Function Mapping via Graph Neural Networks -- Improving Phenotype Prediction using Long-Range Spatio-Temporal Dynamics of Functional Connectivity -- H3K27M Mutations Prediction for Brainstem Gliomas Based on Diffusion Radiomics Learning -- Constrained Learning of Task-related and Spatially-Coherent Dictionaries from Task fMRI Data.
Contained By:	Springer Nature eBook
標題:	Diagnostic imaging - Congresses. - Digital techniques -
電子資源:	https://doi.org/10.1007/978-3-030-87586-2
ISBN:	9783030875862

Machine learning in clinical neuroimaging = 4th International Workshop, MLCN 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
Machine learning in clinical neuroimaging4th International Workshop, MLCN 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /[electronic resource] :MLCN 2021edited by Ahmed Abdulkadir ... [et al.]. - Cham :Springer International Publishing :2021. - xi, 176 p. :ill., digital ;24 cm. - Lecture notes in computer science,130010302-9743 ;. - Lecture notes in computer science ;13001..

Computational Anatomy -- Unfolding the medial temporal lobe cortex to characterize neurodegeneration due to Alzheimer's disease pathology using ex vivo imaging -- Distinguishing Healthy Ageing from Dementia: a Biomechanical Simulation of Brain Atrophy using Deep Networks -- Towards Self-Explainable Classifiers and Regressors in Neuroimaging with Normalizing Flows -- Patch vs. global image-based unsupervised anomaly detection in MR brain scans of early Parkinsonian patients -- MRI image registration considerably improves CNN-based disease classification -- Dynamic Sub-graph Learning for Patch-based Cortical Folding Classification -- Detection of abnormal folding patterns with unsupervised deep generative models -- PialNN: A Fast Deep Learning Framework for Cortical Pial Surface Reconstruction -- Multi-Modal Brain Segmentation Using Hyper-Fused Convolutional Neural Network -- Robust Hydrocephalus Brain Segmentation via Globally and Locally Spatial Guidance -- Brain Networks and Time Series -- Geometric Deep Learning of the Human Connectome Project Multimodal Cortical Parcellation -- Deep Stacking Networks for Conditional Nonlinear Granger Causal Modeling of fMRI Data -- Dynamic Adaptive Spatio-temporal Graph Convolution for fMRI Modelling -- Structure-Function Mapping via Graph Neural Networks -- Improving Phenotype Prediction using Long-Range Spatio-Temporal Dynamics of Functional Connectivity -- H3K27M Mutations Prediction for Brainstem Gliomas Based on Diffusion Radiomics Learning -- Constrained Learning of Task-related and Spatially-Coherent Dictionaries from Task fMRI Data.

This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2021, held on September 27, 2021, in conjunction with MICCAI 2021. The workshop was held virtually due to the COVID-19 pandemic. The 17 papers presented in this book were carefully reviewed and selected from 27 submissions. They were organized in topical sections named: computational anatomy and brain networks and time series.

ISBN: 9783030875862

Standard No.: 10.1007/978-3-030-87586-2doiSubjects--Topical Terms:

893046
Diagnostic imaging
--Digital techniques--Congresses.

LC Class. No.: Q325.5 / .M53 2021

Dewey Class. No.: 006.31

Machine learning in clinical neuroimaging = 4th International Workshop, MLCN 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
LDR:03387nmm a2200373 a 4500 001 2251224
003 DE-He213
005 20210922072911.0
006 m d
007 cr nn 008maaau
008 220215s2021 sz s 0 eng d
020 $a 9783030875862 $q (electronic bk.)
020 $a 9783030875855 $q (paper)
024 7 $a 10.1007/978-3-030-87586-2 $2 doi
035 $a 978-3-030-87586-2
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5 $b .M53 2021
072 7 $a UYQV $2 bicssc
072 7 $a COM016000 $2 bisacsh
072 7 $a UYQV $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .M685 2021
111 2 $a MLCN (Workshop) $n (4th : $d 2021 : $c Online) $3 3517984
245 1 0 $a Machine learning in clinical neuroimaging $h [electronic resource] : $b 4th International Workshop, MLCN 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings / $c edited by Ahmed Abdulkadir ... [et al.].
246 3 $a MLCN 2021
246 3 $a MICCAI 2021
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xi, 176 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 13001
490 1 $a Image processing, computer vision, pattern recognition, and graphics
505 0 $a Computational Anatomy -- Unfolding the medial temporal lobe cortex to characterize neurodegeneration due to Alzheimer's disease pathology using ex vivo imaging -- Distinguishing Healthy Ageing from Dementia: a Biomechanical Simulation of Brain Atrophy using Deep Networks -- Towards Self-Explainable Classifiers and Regressors in Neuroimaging with Normalizing Flows -- Patch vs. global image-based unsupervised anomaly detection in MR brain scans of early Parkinsonian patients -- MRI image registration considerably improves CNN-based disease classification -- Dynamic Sub-graph Learning for Patch-based Cortical Folding Classification -- Detection of abnormal folding patterns with unsupervised deep generative models -- PialNN: A Fast Deep Learning Framework for Cortical Pial Surface Reconstruction -- Multi-Modal Brain Segmentation Using Hyper-Fused Convolutional Neural Network -- Robust Hydrocephalus Brain Segmentation via Globally and Locally Spatial Guidance -- Brain Networks and Time Series -- Geometric Deep Learning of the Human Connectome Project Multimodal Cortical Parcellation -- Deep Stacking Networks for Conditional Nonlinear Granger Causal Modeling of fMRI Data -- Dynamic Adaptive Spatio-temporal Graph Convolution for fMRI Modelling -- Structure-Function Mapping via Graph Neural Networks -- Improving Phenotype Prediction using Long-Range Spatio-Temporal Dynamics of Functional Connectivity -- H3K27M Mutations Prediction for Brainstem Gliomas Based on Diffusion Radiomics Learning -- Constrained Learning of Task-related and Spatially-Coherent Dictionaries from Task fMRI Data.
520 $a This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2021, held on September 27, 2021, in conjunction with MICCAI 2021. The workshop was held virtually due to the COVID-19 pandemic. The 17 papers presented in this book were carefully reviewed and selected from 27 submissions. They were organized in topical sections named: computational anatomy and brain networks and time series.
650 0 $a Diagnostic imaging $x Digital techniques $v Congresses. $3 893046
650 0 $a Machine learning $x Congresses. $3 576368
650 0 $a Electronic data processing $x Distributed processing $v Congresses. $3 622708
650 1 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 890871
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Bioinformatics. $3 553671
700 1 $a Abdulkadir, Ahmed. $3 3517985
710 2 $a SpringerLink (Online service) $3 836513
711 2 $a International Conference on Medical Image Computing and Computer-Assisted Intervention $n (23rd : $d 2020 : $c Online) $3 3492452
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science ; $v 13001. $3 3517986
830 0 $a Image processing, computer vision, pattern recognition, and graphics. $3 3382509
856 4 0 $u https://doi.org/10.1007/978-3-030-87586-2
950 $a Computer Science (SpringerNature-11645)