國立虎尾科技大學 |

Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy = 4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy/ edited by Dajiang Zhu, Jingwen Yan, Heng Huang, Li Shen, Paul M. Thompson, Carl-Fredrik Westin, Xavier Pennec, Sarang Joshi, Mads Nielsen, Tom Fletcher, Stanley Durrleman, Stefan Sommer.
其他題名:	4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings /
其他作者:	Zhu, Dajiang.
面頁冊數:	XVII, 230 p. 113 illus., 91 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Pattern recognition. -
電子資源:	https://doi.org/10.1007/978-3-030-33226-6
ISBN:	9783030332266

Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy = 4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings /
Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings /[electronic resource] :edited by Dajiang Zhu, Jingwen Yan, Heng Huang, Li Shen, Paul M. Thompson, Carl-Fredrik Westin, Xavier Pennec, Sarang Joshi, Mads Nielsen, Tom Fletcher, Stanley Durrleman, Stefan Sommer. - 1st ed. 2019. - XVII, 230 p. 113 illus., 91 illus. in color.online resource. - Image Processing, Computer Vision, Pattern Recognition, and Graphics ;11846. - Image Processing, Computer Vision, Pattern Recognition, and Graphics ;9219.

MBIA -- Non-rigid Registration of White Matter Tractography Using Coherent Point Drift Algorithm -- An Edge Enhanced SRGAN for MRI Super Resolution in Slice-selection Direction -- Exploring Functional Connectivity Biomarker in Autism Using Group-wise Sparse Representation -- Classifying Stages of Mild Cognitive Impairment via Augmented Graph Embedding -- Mapping the spatio-temporal functional coherence in the resting brain -- Species-Preserved Structural Connections Revealed by Sparse Tensor CCA -- Identification of Abnormal Cortical 3-hinge Folding Patterns on Autism Spectral Brains -- Exploring Brain Hemodynamic Response Patterns Via Deep Recurrent Autoencoder -- 3D Convolutional Long-short Term Memory Network for Spatiotemporal Modeling of fMRI Data -- Biological Knowledge Guided Deep Neural Network for Genotype-Phenotype Association Study -- Learning Human Cognition via fMRI Analysis Using 3D CNN and Graph Neural Network -- CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation -- BrainPainter: A software for the visualisation of brain structures, biomarkers and associated pathological processes -- Structural Similarity based Anatomical and Functional Brain Imaging Fusion -- Multimodal Brain Tumor Segmentation Using Encoder-Decoder with Hierarchical Separable Convolution -- Prioritizing Amyloid Imaging Biomarkers in Alzheimer's Disease via Learning to Rank -- MFCA -- Diffeomorphic Metric Learning and Template Optimization for Registration-Based Predictive Models -- 3D mapping of serial histology sections with anomalies using a novel robust deformable registration algorithm -- Spatiotemporal Modeling for Image Time Series with Appearance Change: Application to Early Brain Development -- Surface Foliation Based Brain Morphometry Analysis -- Mixture Probabilistic Principal Geodesic Analysis -- A Geodesic Mixed Effects Model in Kendall's Shape Space -- An as-invariant-as-possible GL+(3)-based Statistical Shape Model.

This book constitutes the refereed joint proceedings of the 4th International Workshop on Multimodal Brain Image Analysis, MBAI 2019, and the 7th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 16 full papers presented at MBAI 2019 and the 7 full papers presented at MFCA 2019 were carefully reviewed and selected. The MBAI papers intend to move forward the state of the art in multimodal brain image analysis, in terms of analysis methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience, and clinical applications. The MFCA papers are devoted to statistical and geometrical methods for modeling the variability of biological shapes. The goal is to foster the interactions between the mathematical community around shapes and the MICCAI community around computational anatomy applications.

ISBN: 9783030332266

Standard No.: 10.1007/978-3-030-33226-6doiSubjects--Topical Terms:

1253525
Pattern recognition.

LC Class. No.: Q337.5

Dewey Class. No.: 006.4

Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy = 4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings /
LDR:04827nam a22004215i 4500 001 1016210
003 DE-He213
005 20200706041147.0
007 cr nn 008mamaa
008 210106s2019 gw | s |||| 0|eng d
020 $a 9783030332266 $9 978-3-030-33226-6
024 7 $a 10.1007/978-3-030-33226-6 $2 doi
035 $a 978-3-030-33226-6
050 4 $a Q337.5
050 4 $a TK7882.P3
072 7 $a UYQP $2 bicssc
072 7 $a COM016000 $2 bisacsh
072 7 $a UYQP $2 thema
082 0 4 $a 006.4 $2 23
245 1 0 $a Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy $h [electronic resource] : $b 4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings / $c edited by Dajiang Zhu, Jingwen Yan, Heng Huang, Li Shen, Paul M. Thompson, Carl-Fredrik Westin, Xavier Pennec, Sarang Joshi, Mads Nielsen, Tom Fletcher, Stanley Durrleman, Stefan Sommer.
250 $a 1st ed. 2019.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a XVII, 230 p. 113 illus., 91 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Image Processing, Computer Vision, Pattern Recognition, and Graphics ; $v 11846
505 0 $a MBIA -- Non-rigid Registration of White Matter Tractography Using Coherent Point Drift Algorithm -- An Edge Enhanced SRGAN for MRI Super Resolution in Slice-selection Direction -- Exploring Functional Connectivity Biomarker in Autism Using Group-wise Sparse Representation -- Classifying Stages of Mild Cognitive Impairment via Augmented Graph Embedding -- Mapping the spatio-temporal functional coherence in the resting brain -- Species-Preserved Structural Connections Revealed by Sparse Tensor CCA -- Identification of Abnormal Cortical 3-hinge Folding Patterns on Autism Spectral Brains -- Exploring Brain Hemodynamic Response Patterns Via Deep Recurrent Autoencoder -- 3D Convolutional Long-short Term Memory Network for Spatiotemporal Modeling of fMRI Data -- Biological Knowledge Guided Deep Neural Network for Genotype-Phenotype Association Study -- Learning Human Cognition via fMRI Analysis Using 3D CNN and Graph Neural Network -- CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation -- BrainPainter: A software for the visualisation of brain structures, biomarkers and associated pathological processes -- Structural Similarity based Anatomical and Functional Brain Imaging Fusion -- Multimodal Brain Tumor Segmentation Using Encoder-Decoder with Hierarchical Separable Convolution -- Prioritizing Amyloid Imaging Biomarkers in Alzheimer's Disease via Learning to Rank -- MFCA -- Diffeomorphic Metric Learning and Template Optimization for Registration-Based Predictive Models -- 3D mapping of serial histology sections with anomalies using a novel robust deformable registration algorithm -- Spatiotemporal Modeling for Image Time Series with Appearance Change: Application to Early Brain Development -- Surface Foliation Based Brain Morphometry Analysis -- Mixture Probabilistic Principal Geodesic Analysis -- A Geodesic Mixed Effects Model in Kendall's Shape Space -- An as-invariant-as-possible GL+(3)-based Statistical Shape Model.
520 $a This book constitutes the refereed joint proceedings of the 4th International Workshop on Multimodal Brain Image Analysis, MBAI 2019, and the 7th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 16 full papers presented at MBAI 2019 and the 7 full papers presented at MFCA 2019 were carefully reviewed and selected. The MBAI papers intend to move forward the state of the art in multimodal brain image analysis, in terms of analysis methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience, and clinical applications. The MFCA papers are devoted to statistical and geometrical methods for modeling the variability of biological shapes. The goal is to foster the interactions between the mathematical community around shapes and the MICCAI community around computational anatomy applications.
650 0 $a Pattern recognition. $3 1253525
650 0 $a Optical data processing. $3 639187
650 0 $a Artificial intelligence. $3 559380
650 0 $a Computers. $3 565115
650 1 4 $a Pattern Recognition. $3 669796
650 2 4 $a Image Processing and Computer Vision. $3 670819
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Information Systems and Communication Service. $3 669203
700 1 $a Zhu, Dajiang. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1310574
700 1 $a Yan, Jingwen. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1310575
700 1 $a Huang, Heng. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1310576
700 1 $a Shen, Li. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1078101
700 1 $a Thompson, Paul M. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1310577
700 1 $a Westin, Carl-Fredrik. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1255297
700 1 $a Pennec, Xavier. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1255592
700 1 $a Joshi, Sarang. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1310578
700 1 $a Nielsen, Mads. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1310579
700 1 $a Fletcher, Tom. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1255591
700 1 $a Durrleman, Stanley. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 883215
700 1 $a Sommer, Stefan. $e editor. $1 https://orcid.org/0000-0001-6784-0328 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1284933
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030332259
776 0 8 $i Printed edition: $z 9783030332273
830 0 $a Image Processing, Computer Vision, Pattern Recognition, and Graphics ; $v 9219 $3 1253644
856 4 0 $u https://doi.org/10.1007/978-3-030-33226-6
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
912 $a ZDB-2-LNC
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)