國立虎尾科技大學 |

Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 = 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part I /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Medical Image Computing and Computer Assisted Intervention – MICCAI 2019/ edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan.
其他題名:	22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part I /
其他作者:	Shen, Dinggang.
面頁冊數:	XXXVII, 819 p. 345 illus., 294 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Optical data processing. -
電子資源:	https://doi.org/10.1007/978-3-030-32239-7
ISBN:	9783030322397

Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 = 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part I /
Medical Image Computing and Computer Assisted Intervention – MICCAI 201922nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part I /[electronic resource] :edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan. - 1st ed. 2019. - XXXVII, 819 p. 345 illus., 294 illus. in color.online resource. - Image Processing, Computer Vision, Pattern Recognition, and Graphics ;11764. - Image Processing, Computer Vision, Pattern Recognition, and Graphics ;9219.

Optical Imaging -- Enhancing OCT Signal by Fusion of GANs: Improving Statistical Power of Glaucoma Trials -- A Deep Reinforcement Learning Framework for Frame-by-frame Plaque Tracking on Intravascular Optical Coherence Tomography Image -- Multi-Index Optic Disc Quantification via MultiTask Ensemble Learning -- Retinal Abnormalities Recognition Using Regional Multitask Learning -- Unifying Structure Analysis and Surrogate-driven Function Regression for Glaucoma OCT Image Screening -- Evaluation of Retinal Image Quality Assessment Networks in Different Color-spaces -- 3D Surface-Based Geometric and Topological Quantification of Retinal Microvasculature in OCT-Angiography via Reeb Analysis -- Limited-Angle Diffuse Optical Tomography Image Reconstruction using Deep Learning -- Data-driven Enhancement of Blurry Retinal Images via Generative Adversarial Networks -- Dual Encoding U-Net for Retinal Vessel Segmentation -- A Deep Learning Design for improving Topology Coherence in Blood Vessel Segmentation -- Boundary and Entropy-driven Adversarial Learning for Fundus Image Segmentation -- Unsupervised Ensemble Strategy for Retinal Vessel Segmentation -- Fully convolutional boundary regression for retina OCT segmentation -- PM-NET: Pyramid Multi-Label Network for Optic Disc and Cup Segmentation -- Biological Age Estimated from Retinal Imaging: A Novel Biomarker of Aging -- Task Adaptive Metric Space for Medium-Shot Medical Image Classification -- Two-Stream CNN with Loose Pair Training for Multi-modal AMD Categorization -- Deep Multi Label Classification in Affine Subspaces -- Multi-scale Microaneurysms Segmentation Using Embedding Triplet Loss -- A Divide-and-Conquer Approach towards Understanding Deep Networks -- Multiclass segmentation as multitask learning for drusen segmentation in retinal optical coherence tomography -- Active Appearance Model Induced Generative Adversarial Networks for Controlled Data Augmentation -- Biomarker Localization by Combining CNN Classifier and Generative Adversarial Network -- Probabilistic Atlases to Enforce Topological Constraints -- Synapse-Aware Skeleton Generation for Neural Circuits -- Seeing Under the Cover: A Physics Guided Learning Approach for In-Bed Pose Estimation -- EDA-Net: Dense Aggregation of Deep and Shallow Information Achieves Quantitative Photoacoustic Blood Oxygenation Imaging Deep in Human Breast -- Fused Detection of Retinal Biomarkers in OCT Volumes -- Vessel-Net: Retinal Vessel Segmentation under Multi-path Supervision -- Ki-GAN: Knowledge Infusion Generative Adversarial Network for Photoacoustic Image Reconstruction in vivo -- Uncertainty guided semisupervised segmentation of retinal layers in OCT images -- Endoscopy -- Triple ANet: Adaptive Abnormal-aware Attention Network for WCE Image Classification -- Selective Feature Aggregation Network with Area-boundary Constraints for Polyp Segmentation -- Deep Sequential Mosaicking of Fetoscopic Videos -- Landmark-guided Deformable Image Registration for Supervised Autonomous Robotic Tumor Resection -- Multi-View Learning with Feature Level Fusion for Cervical Dysplasia Diagnosis -- Real-time Surface Deformation Recovery from Stereo Videos -- Microscopy -- Rectified Cross-Entropy and Upper Transition Loss for Weakly Supervised Whole Slide Image Classifier -- From Whole Slide Imaging to Microscopy: Deep Microscopy Adaptation Network for Histopathology Cancer Image Classification -- Multi-scale Cell Instance Segmentation with Keypoint Graph based Bounding Boxes -- Improving Nuclei/Gland Instance Segmentation in Histopathology Images by Full Resolution Neural Network and Spatial Constrained Loss -- Synthetic Augmentation and Feature-based Filtering for Improved Cervical Histopathology Image Classification -- Cell Tracking with Deep Learning for Cell Detection and Motion Estimation in Low-Frame-Rate -- Accelerated ML-assisted Tumor Detection in High-Resolution Histopathology Images -- Pre-operative Overall Survival Time Prediction for Glioblastoma Patients Using Deep Learning on Both Imaging Phenotype and Genotype -- Pathology-aware deep network visualization and its application in glaucoma image synthesis -- CORAL8: Concurrent Object Regression for Area Localization in Medical Image Panels -- ET-Net: A Generic Edge-Attention Guidance Network for Medical Image Segmentation -- Instance Segmentation of Biomedical Images with an Object-aware Embedding Learned with Local Constraints -- Diverse Multiple Prediction on Neural Image Reconstruction -- Deep Segmentation-Emendation Model for Gland Instance Segmentation -- Fast and Accurate Electron Microscopy Image Registration with 3D Convolution -- PlacentaNet: Automatic Morphological Characterization of Placenta Photos with Deep Learning -- Deep Multi-Instance Learning for survival prediction from Whole Slide Images -- High-Resolution Diabetic Retinopathy Image Synthesis Manipulated by Grading and Lesions -- Deep Instance-Level Hard Negative Mining Model for Histopathology Images -- Synthetic patches, real images: screening for centrosome aberrations in EM images of human cancer cells -- Patch Transformer for Multi-tagging Whole Slide Histopathology Images -- Pancreatic Cancer Detection in Whole Slide Images Using Noisy Label Annotations -- Encoding histopathological WSIs using GNN for scalable diagnostically relevant regions retrieval -- Local and Global Consistency Regularized Mean Teacher for Semi-supervised Nuclei Classification -- Perceptual Embedding Consistency for Seamless Reconstruction of Tilewise Style Transfer -- Precise Separation of Adjacent Nuclei using a Siamese Neural Network -- PFA-ScanNet: Pyramidal Feature Aggregation with Synergistic Learning for Breast Cancer Metastasis Analysis -- DeepACE: Automated Chromosome Enumeration in Metaphase Cell Images Using Deep Convolutional Neural Networks -- Unsupervised Subtyping of Cholangiocarcinoma Using A Deep Clustering Convolutional Autoencoder -- Evidence Localization for Pathology Images using Weakly Supervised Learning -- Nuclear Instance Segmentation using a Proposal-Free Spatially Aware Deep Learning Framework -- GAN-Based Image Enrichment in Digital Pathology Boosts Segmentation Accuracy -- IRNet: Instance Relation Network for Overlapping Cervical Cell Segmentation -- Weakly Supervised Cell Segmentation in Dense by Propagating from Detection Map -- Understanding Fixation in Fluorescence Microscopy via Robust Non-negative Tensor Factorization, Atlas-based Motion Correction and Functional Statistics -- ConCORDe-Net: Cell Count Regularized Convolutional Neural Network for Cell Detection, and Cell Classification in Multiplex Immunohistochemistry Images -- Multi-task learning of a deep K-nearest neighbour network for histopathological image classification and retrieval -- Multiclass deep active learning for detecting red blood cell subtypes in brightfield microscopy images -- Enhanced Cycle-Consistent Generative Adversarial Network for Color Normalization of H&E Stained Images -- Nuclei Segmentation in Histopathological Images using Two-Stage Learning -- ACE-Net: Biomedical Image Segmentation with Augmented Contracting and Expansive Paths -- CS-Net: Channel and Spatial Attention Network for Curvilinear Structure Segmentation -- PseudoEdgeNet: Nuclei Segmentation only with Point Annotations -- Adversarial Domain Adaptation and Pseudo-Labeling for Cross-Modality Microscopy Image Quantification -- Progressive Learning for Neuronal Population Reconstruction from Optical Microscopy Images -- Whole-Sample Mapping of Cancerous and Benign Tissue Properties -- Multi-Task Neural Networks with Spatial Activation for Retinal Vessel Segmentation and Artery/Vein Classification -- Fine-Scale Vessel Extraction in Fundus Images by Registration with Fluorescein Angiography -- DME-Net: Diabetic Macular Edema Grading by Auxiliary Task Learning -- Attention Guided Network for Retinal Image Segmentation -- An unsupervised domain adaptation approach to classification of stem cell-derived cardiomyocytes.

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019. The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: optical imaging; endoscopy; microscopy. Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression. Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging. Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis. Part V: computer assisted interventions; MIC meets CAI. Part VI: computed tomography; X-ray imaging.

ISBN: 9783030322397

Standard No.: 10.1007/978-3-030-32239-7doiSubjects--Topical Terms:

639187
Optical data processing.

LC Class. No.: TA1630-1650

Dewey Class. No.: 006.6

Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 = 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part I /
LDR:10763nam a22004335i 4500 001 1016209
003 DE-He213
005 20200630024959.0
007 cr nn 008mamaa
008 210106s2019 gw | s |||| 0|eng d
020 $a 9783030322397 $9 978-3-030-32239-7
024 7 $a 10.1007/978-3-030-32239-7 $2 doi
035 $a 978-3-030-32239-7
050 4 $a TA1630-1650
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
082 0 4 $a 006.37 $2 23
245 1 0 $a Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 $h [electronic resource] : $b 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part I / $c edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan.
250 $a 1st ed. 2019.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a XXXVII, 819 p. 345 illus., 294 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 11764
505 0 $a Optical Imaging -- Enhancing OCT Signal by Fusion of GANs: Improving Statistical Power of Glaucoma Trials -- A Deep Reinforcement Learning Framework for Frame-by-frame Plaque Tracking on Intravascular Optical Coherence Tomography Image -- Multi-Index Optic Disc Quantification via MultiTask Ensemble Learning -- Retinal Abnormalities Recognition Using Regional Multitask Learning -- Unifying Structure Analysis and Surrogate-driven Function Regression for Glaucoma OCT Image Screening -- Evaluation of Retinal Image Quality Assessment Networks in Different Color-spaces -- 3D Surface-Based Geometric and Topological Quantification of Retinal Microvasculature in OCT-Angiography via Reeb Analysis -- Limited-Angle Diffuse Optical Tomography Image Reconstruction using Deep Learning -- Data-driven Enhancement of Blurry Retinal Images via Generative Adversarial Networks -- Dual Encoding U-Net for Retinal Vessel Segmentation -- A Deep Learning Design for improving Topology Coherence in Blood Vessel Segmentation -- Boundary and Entropy-driven Adversarial Learning for Fundus Image Segmentation -- Unsupervised Ensemble Strategy for Retinal Vessel Segmentation -- Fully convolutional boundary regression for retina OCT segmentation -- PM-NET: Pyramid Multi-Label Network for Optic Disc and Cup Segmentation -- Biological Age Estimated from Retinal Imaging: A Novel Biomarker of Aging -- Task Adaptive Metric Space for Medium-Shot Medical Image Classification -- Two-Stream CNN with Loose Pair Training for Multi-modal AMD Categorization -- Deep Multi Label Classification in Affine Subspaces -- Multi-scale Microaneurysms Segmentation Using Embedding Triplet Loss -- A Divide-and-Conquer Approach towards Understanding Deep Networks -- Multiclass segmentation as multitask learning for drusen segmentation in retinal optical coherence tomography -- Active Appearance Model Induced Generative Adversarial Networks for Controlled Data Augmentation -- Biomarker Localization by Combining CNN Classifier and Generative Adversarial Network -- Probabilistic Atlases to Enforce Topological Constraints -- Synapse-Aware Skeleton Generation for Neural Circuits -- Seeing Under the Cover: A Physics Guided Learning Approach for In-Bed Pose Estimation -- EDA-Net: Dense Aggregation of Deep and Shallow Information Achieves Quantitative Photoacoustic Blood Oxygenation Imaging Deep in Human Breast -- Fused Detection of Retinal Biomarkers in OCT Volumes -- Vessel-Net: Retinal Vessel Segmentation under Multi-path Supervision -- Ki-GAN: Knowledge Infusion Generative Adversarial Network for Photoacoustic Image Reconstruction in vivo -- Uncertainty guided semisupervised segmentation of retinal layers in OCT images -- Endoscopy -- Triple ANet: Adaptive Abnormal-aware Attention Network for WCE Image Classification -- Selective Feature Aggregation Network with Area-boundary Constraints for Polyp Segmentation -- Deep Sequential Mosaicking of Fetoscopic Videos -- Landmark-guided Deformable Image Registration for Supervised Autonomous Robotic Tumor Resection -- Multi-View Learning with Feature Level Fusion for Cervical Dysplasia Diagnosis -- Real-time Surface Deformation Recovery from Stereo Videos -- Microscopy -- Rectified Cross-Entropy and Upper Transition Loss for Weakly Supervised Whole Slide Image Classifier -- From Whole Slide Imaging to Microscopy: Deep Microscopy Adaptation Network for Histopathology Cancer Image Classification -- Multi-scale Cell Instance Segmentation with Keypoint Graph based Bounding Boxes -- Improving Nuclei/Gland Instance Segmentation in Histopathology Images by Full Resolution Neural Network and Spatial Constrained Loss -- Synthetic Augmentation and Feature-based Filtering for Improved Cervical Histopathology Image Classification -- Cell Tracking with Deep Learning for Cell Detection and Motion Estimation in Low-Frame-Rate -- Accelerated ML-assisted Tumor Detection in High-Resolution Histopathology Images -- Pre-operative Overall Survival Time Prediction for Glioblastoma Patients Using Deep Learning on Both Imaging Phenotype and Genotype -- Pathology-aware deep network visualization and its application in glaucoma image synthesis -- CORAL8: Concurrent Object Regression for Area Localization in Medical Image Panels -- ET-Net: A Generic Edge-Attention Guidance Network for Medical Image Segmentation -- Instance Segmentation of Biomedical Images with an Object-aware Embedding Learned with Local Constraints -- Diverse Multiple Prediction on Neural Image Reconstruction -- Deep Segmentation-Emendation Model for Gland Instance Segmentation -- Fast and Accurate Electron Microscopy Image Registration with 3D Convolution -- PlacentaNet: Automatic Morphological Characterization of Placenta Photos with Deep Learning -- Deep Multi-Instance Learning for survival prediction from Whole Slide Images -- High-Resolution Diabetic Retinopathy Image Synthesis Manipulated by Grading and Lesions -- Deep Instance-Level Hard Negative Mining Model for Histopathology Images -- Synthetic patches, real images: screening for centrosome aberrations in EM images of human cancer cells -- Patch Transformer for Multi-tagging Whole Slide Histopathology Images -- Pancreatic Cancer Detection in Whole Slide Images Using Noisy Label Annotations -- Encoding histopathological WSIs using GNN for scalable diagnostically relevant regions retrieval -- Local and Global Consistency Regularized Mean Teacher for Semi-supervised Nuclei Classification -- Perceptual Embedding Consistency for Seamless Reconstruction of Tilewise Style Transfer -- Precise Separation of Adjacent Nuclei using a Siamese Neural Network -- PFA-ScanNet: Pyramidal Feature Aggregation with Synergistic Learning for Breast Cancer Metastasis Analysis -- DeepACE: Automated Chromosome Enumeration in Metaphase Cell Images Using Deep Convolutional Neural Networks -- Unsupervised Subtyping of Cholangiocarcinoma Using A Deep Clustering Convolutional Autoencoder -- Evidence Localization for Pathology Images using Weakly Supervised Learning -- Nuclear Instance Segmentation using a Proposal-Free Spatially Aware Deep Learning Framework -- GAN-Based Image Enrichment in Digital Pathology Boosts Segmentation Accuracy -- IRNet: Instance Relation Network for Overlapping Cervical Cell Segmentation -- Weakly Supervised Cell Segmentation in Dense by Propagating from Detection Map -- Understanding Fixation in Fluorescence Microscopy via Robust Non-negative Tensor Factorization, Atlas-based Motion Correction and Functional Statistics -- ConCORDe-Net: Cell Count Regularized Convolutional Neural Network for Cell Detection, and Cell Classification in Multiplex Immunohistochemistry Images -- Multi-task learning of a deep K-nearest neighbour network for histopathological image classification and retrieval -- Multiclass deep active learning for detecting red blood cell subtypes in brightfield microscopy images -- Enhanced Cycle-Consistent Generative Adversarial Network for Color Normalization of H&E Stained Images -- Nuclei Segmentation in Histopathological Images using Two-Stage Learning -- ACE-Net: Biomedical Image Segmentation with Augmented Contracting and Expansive Paths -- CS-Net: Channel and Spatial Attention Network for Curvilinear Structure Segmentation -- PseudoEdgeNet: Nuclei Segmentation only with Point Annotations -- Adversarial Domain Adaptation and Pseudo-Labeling for Cross-Modality Microscopy Image Quantification -- Progressive Learning for Neuronal Population Reconstruction from Optical Microscopy Images -- Whole-Sample Mapping of Cancerous and Benign Tissue Properties -- Multi-Task Neural Networks with Spatial Activation for Retinal Vessel Segmentation and Artery/Vein Classification -- Fine-Scale Vessel Extraction in Fundus Images by Registration with Fluorescein Angiography -- DME-Net: Diabetic Macular Edema Grading by Auxiliary Task Learning -- Attention Guided Network for Retinal Image Segmentation -- An unsupervised domain adaptation approach to classification of stem cell-derived cardiomyocytes.
520 $a The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019. The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: optical imaging; endoscopy; microscopy. Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression. Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging. Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis. Part V: computer assisted interventions; MIC meets CAI. Part VI: computed tomography; X-ray imaging.
650 0 $a Optical data processing. $3 639187
650 0 $a Pattern recognition. $3 1253525
650 0 $a Artificial intelligence. $3 559380
650 0 $a Health informatics. $3 1064466
650 1 4 $a Image Processing and Computer Vision. $3 670819
650 2 4 $a Pattern Recognition. $3 669796
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Health Informatics. $3 593963
700 1 $a Shen, Dinggang. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1138691
700 1 $a Liu, Tianming. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 815939
700 1 $a Peters, Terry M. $e editor. $1 https://orcid.org/0000-0003-1440-7488 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1304152
700 1 $a Staib, Lawrence H. $e editor. $1 https://orcid.org/0000-0002-9516-5136 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1304153
700 1 $a Essert, Caroline. $e editor. $1 https://orcid.org/0000-0003-2572-9730 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1304154
700 1 $a Zhou, Sean. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1304155
700 1 $a Yap, Pew-Thian. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 883212
700 1 $a Khan, Ali. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1304156
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030322380
776 0 8 $i Printed edition: $z 9783030322403
830 0 $a Image Processing, Computer Vision, Pattern Recognition, and Graphics ; $v 9219 $3 1253644
856 4 0 $u https://doi.org/10.1007/978-3-030-32239-7
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)