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

Medical image computing and computer...

International Conference on Medical Image Computing and Computer-Assisted Intervention (2022 :)

FindBook

Google Book

Amazon

博客來

Medical image computing and computer assisted intervention - MICCAI 2022 = 25th International Conference, Singapore, September 18-22, 2022 : proceedings.. Part I /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Medical image computing and computer assisted intervention - MICCAI 2022/ edited by Linwei Wang ... [et al.].
其他題名:	25th International Conference, Singapore, September 18-22, 2022 : proceedings.
其他題名:	MICCAI 2022
其他作者:	Wang, Linwei.
團體作者:	International Conference on Medical Image Computing and Computer-Assisted Intervention
出版者:	Cham :Springer Nature Switzerland : : 2022.,
面頁冊數:	xl, 768 p. :ill. (some col.), digital ;24 cm.
內容註:	Brain Development and Atlases -- Progression models for imaging data with Longitudinal Variational Auto Encoders -- Boundary-Enhanced Self-Supervised Learning for Brain Structure Segmentation -- Domain-Prior-Induced Structural MRI Adaptation for Clinical Progression Prediction of Subjective Cognitive Decline -- 3D Global Fourier Network for Alzheimer's Disease Diagnosis using Structural MRI -- CASHformer: Cognition Aware SHape Transformer for Longitudinal Analysis -- Interpretable differential diagnosis for Alzheimer's disease and Frontotemporal dementia -- Is a PET all you need? A multi-modal study for Alzheimer's disease using 3D CNNs -- Unsupervised Representation Learning of Cingulate Cortical Folding Patterns -- Feature robustness and sex differences in medical imaging: a case study in MRI-based Alzheimer's disease detection -- Extended Electrophysiological Source Imaging with Spatial Graph Filters -- DWI and Tractography -- Hybrid Graph Transformer for Tissue Microstructure Estimation with Undersampled Diffusion MRI Data -- Atlas-powered deep learning (ADL) - application to diffusion weighted MRI -- One-Shot Segmentation of Novel White Matter Tracts via Extensive Data Augmentation -- Accurate Corresponding Fiber Tract Segmentation via FiberGeoMap Learner -- An adaptive network with extragradient for diffusion MRI-based microstructure estimation -- Shape-based features of white matter fiber-tracts associated with outcome in Major Depression Disorder -- White Matter Tracts are Point Clouds: Neuropsychological Score Prediction and Critical Region Localization via Geometric Deep Learning -- Segmentation of Whole-brain Tractography: A Deep Learning Algorithm Based on 3D Raw Curve Points -- TractoFormer: A Novel Fiber-level Whole Brain Tractography Analysis Framework Using Spectral Embedding and Vision Transformers -- Multi-site Normative Modeling of Diffusion Tensor Imaging Metrics Using Hierarchical Bayesian Regression -- Functional Brain Networks -- Contrastive Functional Connectivity Graph Learning for Population-based fMRI Classification -- Joint Graph Convolution for Analyzing Brain Structural and Functional Connectome -- Decoding Task Sub-type States with Group Deep Bidirectional Recurrent Neural Network -- Hierarchical Brain Networks Decomposition via Prior Knowledge Guided Deep Belief Network -- Interpretable signature of consciousness in resting-state functional network brain activity -- Nonlinear Conditional Time-varying Granger Causality of Task fMRI via Deep Stacking Networks and Adaptive Convolutional Kernels -- fMRI Neurofeedback Learning Patterns are Predictive of Personal and Clinical Traits -- Multi-head Attention-based Masked Sequence Model for Mapping Functional Brain Networks -- Dual-HINet: Dual Hierarchical Integration Network of Multigraphs for Connectional Brain Template Learning -- RefineNet: An Automated Framework to Generate Task and Subject-Specific Brain Parcellations for Resting-State fMRI Analysis -- Modelling Cycles in Brain Networks with the Hodge Laplacian -- Predicting Spatio-Temporal Human Brain Response Using fMRI -- Revealing Continuous Brain Dynamical Organization with Multimodal Graph Transformer -- Explainable Contrastive Multiview Graph Representation of Brain, Mind, and Behavior -- Embedding Human Brain Function via Transformer -- How Much to Aggregate: Learning Adaptive Node-wise Scales on Graphs for Brain Networks -- Combining multiple atlases to estimate data-driven mappings between functional connectomes using optimal transport -- The Semi-constrained Network-Based Statistic (scNBS): integrating local and global information for brain network inference -- Unified Embeddings of Structural and Functional Connectome via a Function-Constrained Structural Graph Variational Auto-Encoder -- Neuroimaging -- Characterization of brain activity patterns across states of consciousness based on variational auto-encoders -- Conditional VAEs for confound removal and normative modelling of neurodegenerative diseases -- Semi-supervised learning with data harmonisation for biomarker discovery from resting state fMRI -- Cerebral Microbleeds Detection Using a 3D Feature Fused Region Proposal Network with Hard Sample Prototype Learning -- Brain-Aware Replacements for Supervised Contrastive Learning in Detection of Alzheimer's Disease -- Heart and Lung Imaging -- AANet: Artery-Aware Network for Pulmonary Embolism Detection in CTPA Images -- Siamese Encoder-based Spatial-Temporal Mixer for Growth Trend Prediction of Lung Nodules on CT Scans -- What Makes for Automatic Reconstruction of Pulmonary Segments -- CFDA: Collaborative Feature Disentanglement and Augmentation for Pulmonary Airway Tree Modeling of COVID-19 CTs -- Decoupling Predictions in Distributed Learning for Multi-Center Left Atrial MRI Segmentation -- Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision -- Diffusion Deformable Model for 4D Temporal Medical Image Generation -- SAPJNet: Sequence-Adaptive Prototype-Joint Network for Small Sample Multi-Sequence MRI Diagnosis -- Evolutionary Multi-objective Architecture Search Framework: Application to COVID-19 3D CT Classification -- Detecting Aortic Valve Pathology from the 3-Chamber Cine Cardiac MRI View -- CheXRelNet: An Anatomy-Aware Model for Tracking Longitudinal Relationships between Chest X-Rays -- Reinforcement learning for active modality selection during diagnosis -- Ensembled Prediction of Rheumatic Heart Disease from Ungated Doppler Echocardiography Acquired in Low-Resource Settings -- Attention mechanisms for physiological signal deep learning: which attention should we take? -- Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance -- Multimodal Contrastive Learning for Prospective Personalized Estimation of CT Organ Dose -- RTN: Reinforced Transformer Network for Coronary CT Angiography Vessel-level Image Quality Assessment -- A Comprehensive Study of Modern Architectures and Regularization Approaches on CheXpert5000 -- LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule Detection -- Consistency-based Semi-supervised Evidential Active Learning for Diagnostic Radiograph Classification -- Self-Rating Curriculum Learning for Localization and Segmentation of Tuberculosis on Chest Radiograph -- Rib Suppression in Digital Chest Tomosynthesis -- Multi-Task Lung Nodule Detection in Chest Radiographs with a Dual Head Network -- Dermatology -- Data-Driven Deep Supervision for Skin Lesion Classification -- Out-of-Distribution Detection for Long-tailed and Fine-grained Skin Lesion Images -- FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis -- Reliability-aware Contrastive Self-ensembling for Semi-supervised Medical Image Classification.
Contained By:	Springer Nature eBook
標題:	Diagnostic imaging - Congresses. - Data processing -
電子資源:	https://doi.org/10.1007/978-3-031-16431-6
ISBN:	9783031164316

Medical image computing and computer assisted intervention - MICCAI 2022 = 25th International Conference, Singapore, September 18-22, 2022 : proceedings.. Part I /
Medical image computing and computer assisted intervention - MICCAI 202225th International Conference, Singapore, September 18-22, 2022 : proceedings.Part I /[electronic resource] :MICCAI 2022edited by Linwei Wang ... [et al.]. - Cham :Springer Nature Switzerland :2022. - xl, 768 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,134310302-9743 ;. - Lecture notes in computer science ;13431..

Brain Development and Atlases -- Progression models for imaging data with Longitudinal Variational Auto Encoders -- Boundary-Enhanced Self-Supervised Learning for Brain Structure Segmentation -- Domain-Prior-Induced Structural MRI Adaptation for Clinical Progression Prediction of Subjective Cognitive Decline -- 3D Global Fourier Network for Alzheimer's Disease Diagnosis using Structural MRI -- CASHformer: Cognition Aware SHape Transformer for Longitudinal Analysis -- Interpretable differential diagnosis for Alzheimer's disease and Frontotemporal dementia -- Is a PET all you need? A multi-modal study for Alzheimer's disease using 3D CNNs -- Unsupervised Representation Learning of Cingulate Cortical Folding Patterns -- Feature robustness and sex differences in medical imaging: a case study in MRI-based Alzheimer's disease detection -- Extended Electrophysiological Source Imaging with Spatial Graph Filters -- DWI and Tractography -- Hybrid Graph Transformer for Tissue Microstructure Estimation with Undersampled Diffusion MRI Data -- Atlas-powered deep learning (ADL) - application to diffusion weighted MRI -- One-Shot Segmentation of Novel White Matter Tracts via Extensive Data Augmentation -- Accurate Corresponding Fiber Tract Segmentation via FiberGeoMap Learner -- An adaptive network with extragradient for diffusion MRI-based microstructure estimation -- Shape-based features of white matter fiber-tracts associated with outcome in Major Depression Disorder -- White Matter Tracts are Point Clouds: Neuropsychological Score Prediction and Critical Region Localization via Geometric Deep Learning -- Segmentation of Whole-brain Tractography: A Deep Learning Algorithm Based on 3D Raw Curve Points -- TractoFormer: A Novel Fiber-level Whole Brain Tractography Analysis Framework Using Spectral Embedding and Vision Transformers -- Multi-site Normative Modeling of Diffusion Tensor Imaging Metrics Using Hierarchical Bayesian Regression -- Functional Brain Networks -- Contrastive Functional Connectivity Graph Learning for Population-based fMRI Classification -- Joint Graph Convolution for Analyzing Brain Structural and Functional Connectome -- Decoding Task Sub-type States with Group Deep Bidirectional Recurrent Neural Network -- Hierarchical Brain Networks Decomposition via Prior Knowledge Guided Deep Belief Network -- Interpretable signature of consciousness in resting-state functional network brain activity -- Nonlinear Conditional Time-varying Granger Causality of Task fMRI via Deep Stacking Networks and Adaptive Convolutional Kernels -- fMRI Neurofeedback Learning Patterns are Predictive of Personal and Clinical Traits -- Multi-head Attention-based Masked Sequence Model for Mapping Functional Brain Networks -- Dual-HINet: Dual Hierarchical Integration Network of Multigraphs for Connectional Brain Template Learning -- RefineNet: An Automated Framework to Generate Task and Subject-Specific Brain Parcellations for Resting-State fMRI Analysis -- Modelling Cycles in Brain Networks with the Hodge Laplacian -- Predicting Spatio-Temporal Human Brain Response Using fMRI -- Revealing Continuous Brain Dynamical Organization with Multimodal Graph Transformer -- Explainable Contrastive Multiview Graph Representation of Brain, Mind, and Behavior -- Embedding Human Brain Function via Transformer -- How Much to Aggregate: Learning Adaptive Node-wise Scales on Graphs for Brain Networks -- Combining multiple atlases to estimate data-driven mappings between functional connectomes using optimal transport -- The Semi-constrained Network-Based Statistic (scNBS): integrating local and global information for brain network inference -- Unified Embeddings of Structural and Functional Connectome via a Function-Constrained Structural Graph Variational Auto-Encoder -- Neuroimaging -- Characterization of brain activity patterns across states of consciousness based on variational auto-encoders -- Conditional VAEs for confound removal and normative modelling of neurodegenerative diseases -- Semi-supervised learning with data harmonisation for biomarker discovery from resting state fMRI -- Cerebral Microbleeds Detection Using a 3D Feature Fused Region Proposal Network with Hard Sample Prototype Learning -- Brain-Aware Replacements for Supervised Contrastive Learning in Detection of Alzheimer's Disease -- Heart and Lung Imaging -- AANet: Artery-Aware Network for Pulmonary Embolism Detection in CTPA Images -- Siamese Encoder-based Spatial-Temporal Mixer for Growth Trend Prediction of Lung Nodules on CT Scans -- What Makes for Automatic Reconstruction of Pulmonary Segments -- CFDA: Collaborative Feature Disentanglement and Augmentation for Pulmonary Airway Tree Modeling of COVID-19 CTs -- Decoupling Predictions in Distributed Learning for Multi-Center Left Atrial MRI Segmentation -- Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision -- Diffusion Deformable Model for 4D Temporal Medical Image Generation -- SAPJNet: Sequence-Adaptive Prototype-Joint Network for Small Sample Multi-Sequence MRI Diagnosis -- Evolutionary Multi-objective Architecture Search Framework: Application to COVID-19 3D CT Classification -- Detecting Aortic Valve Pathology from the 3-Chamber Cine Cardiac MRI View -- CheXRelNet: An Anatomy-Aware Model for Tracking Longitudinal Relationships between Chest X-Rays -- Reinforcement learning for active modality selection during diagnosis -- Ensembled Prediction of Rheumatic Heart Disease from Ungated Doppler Echocardiography Acquired in Low-Resource Settings -- Attention mechanisms for physiological signal deep learning: which attention should we take? -- Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance -- Multimodal Contrastive Learning for Prospective Personalized Estimation of CT Organ Dose -- RTN: Reinforced Transformer Network for Coronary CT Angiography Vessel-level Image Quality Assessment -- A Comprehensive Study of Modern Architectures and Regularization Approaches on CheXpert5000 -- LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule Detection -- Consistency-based Semi-supervised Evidential Active Learning for Diagnostic Radiograph Classification -- Self-Rating Curriculum Learning for Localization and Segmentation of Tuberculosis on Chest Radiograph -- Rib Suppression in Digital Chest Tomosynthesis -- Multi-Task Lung Nodule Detection in Chest Radiographs with a Dual Head Network -- Dermatology -- Data-Driven Deep Supervision for Skin Lesion Classification -- Out-of-Distribution Detection for Long-tailed and Fine-grained Skin Lesion Images -- FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis -- Reliability-aware Contrastive Self-ensembling for Semi-supervised Medical Image Classification.

The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022. The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology; Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging; Part III: Breast imaging; colonoscopy; computer aided diagnosis; Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I; Part V: Image segmentation II; integration of imaging with non-imaging biomarkers; Part VI: Image registration; image reconstruction; Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning - domain adaptation and generalization; Part VIII: Machine learning - weakly-supervised learning; machine learning - model interpretation; machine learning - uncertainty; machine learning theory and methodologies.

ISBN: 9783031164316

Standard No.: 10.1007/978-3-031-16431-6doiSubjects--Topical Terms:

893542
Diagnostic imaging
--Data processing--Congresses.

LC Class. No.: RC78.7.D53 / I58 2022

Dewey Class. No.: 616.0754

Medical image computing and computer assisted intervention - MICCAI 2022 = 25th International Conference, Singapore, September 18-22, 2022 : proceedings.. Part I /
LDR:09466nmm a2200349 a 4500 001 2303928
003 DE-He213
005 20220914220233.0
006 m d
007 cr nn 008maaau
008 230409s2022 sz s 0 eng d
020 $a 9783031164316 $q (electronic bk.)
020 $a 9783031164309 $q (paper)
024 7 $a 10.1007/978-3-031-16431-6 $2 doi
035 $a 978-3-031-16431-6
040 $a GP $c GP
041 0 $a eng
050 4 $a RC78.7.D53 $b I58 2022
072 7 $a UYT $2 bicssc
072 7 $a COM016000 $2 bisacsh
072 7 $a UYT $2 thema
082 0 4 $a 616.0754 $2 23
090 $a RC78.7.D53 $b I61 2022
111 2 $a International Conference on Medical Image Computing and Computer-Assisted Intervention $n (25th : $d 2022 : $c Singapore ; Online) $3 3605665
245 1 0 $a Medical image computing and computer assisted intervention - MICCAI 2022 $h [electronic resource] : $b 25th International Conference, Singapore, September 18-22, 2022 : proceedings. $n Part I / $c edited by Linwei Wang ... [et al.].
246 3 $a MICCAI 2022
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2022.
300 $a xl, 768 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 13431
505 0 $a Brain Development and Atlases -- Progression models for imaging data with Longitudinal Variational Auto Encoders -- Boundary-Enhanced Self-Supervised Learning for Brain Structure Segmentation -- Domain-Prior-Induced Structural MRI Adaptation for Clinical Progression Prediction of Subjective Cognitive Decline -- 3D Global Fourier Network for Alzheimer's Disease Diagnosis using Structural MRI -- CASHformer: Cognition Aware SHape Transformer for Longitudinal Analysis -- Interpretable differential diagnosis for Alzheimer's disease and Frontotemporal dementia -- Is a PET all you need? A multi-modal study for Alzheimer's disease using 3D CNNs -- Unsupervised Representation Learning of Cingulate Cortical Folding Patterns -- Feature robustness and sex differences in medical imaging: a case study in MRI-based Alzheimer's disease detection -- Extended Electrophysiological Source Imaging with Spatial Graph Filters -- DWI and Tractography -- Hybrid Graph Transformer for Tissue Microstructure Estimation with Undersampled Diffusion MRI Data -- Atlas-powered deep learning (ADL) - application to diffusion weighted MRI -- One-Shot Segmentation of Novel White Matter Tracts via Extensive Data Augmentation -- Accurate Corresponding Fiber Tract Segmentation via FiberGeoMap Learner -- An adaptive network with extragradient for diffusion MRI-based microstructure estimation -- Shape-based features of white matter fiber-tracts associated with outcome in Major Depression Disorder -- White Matter Tracts are Point Clouds: Neuropsychological Score Prediction and Critical Region Localization via Geometric Deep Learning -- Segmentation of Whole-brain Tractography: A Deep Learning Algorithm Based on 3D Raw Curve Points -- TractoFormer: A Novel Fiber-level Whole Brain Tractography Analysis Framework Using Spectral Embedding and Vision Transformers -- Multi-site Normative Modeling of Diffusion Tensor Imaging Metrics Using Hierarchical Bayesian Regression -- Functional Brain Networks -- Contrastive Functional Connectivity Graph Learning for Population-based fMRI Classification -- Joint Graph Convolution for Analyzing Brain Structural and Functional Connectome -- Decoding Task Sub-type States with Group Deep Bidirectional Recurrent Neural Network -- Hierarchical Brain Networks Decomposition via Prior Knowledge Guided Deep Belief Network -- Interpretable signature of consciousness in resting-state functional network brain activity -- Nonlinear Conditional Time-varying Granger Causality of Task fMRI via Deep Stacking Networks and Adaptive Convolutional Kernels -- fMRI Neurofeedback Learning Patterns are Predictive of Personal and Clinical Traits -- Multi-head Attention-based Masked Sequence Model for Mapping Functional Brain Networks -- Dual-HINet: Dual Hierarchical Integration Network of Multigraphs for Connectional Brain Template Learning -- RefineNet: An Automated Framework to Generate Task and Subject-Specific Brain Parcellations for Resting-State fMRI Analysis -- Modelling Cycles in Brain Networks with the Hodge Laplacian -- Predicting Spatio-Temporal Human Brain Response Using fMRI -- Revealing Continuous Brain Dynamical Organization with Multimodal Graph Transformer -- Explainable Contrastive Multiview Graph Representation of Brain, Mind, and Behavior -- Embedding Human Brain Function via Transformer -- How Much to Aggregate: Learning Adaptive Node-wise Scales on Graphs for Brain Networks -- Combining multiple atlases to estimate data-driven mappings between functional connectomes using optimal transport -- The Semi-constrained Network-Based Statistic (scNBS): integrating local and global information for brain network inference -- Unified Embeddings of Structural and Functional Connectome via a Function-Constrained Structural Graph Variational Auto-Encoder -- Neuroimaging -- Characterization of brain activity patterns across states of consciousness based on variational auto-encoders -- Conditional VAEs for confound removal and normative modelling of neurodegenerative diseases -- Semi-supervised learning with data harmonisation for biomarker discovery from resting state fMRI -- Cerebral Microbleeds Detection Using a 3D Feature Fused Region Proposal Network with Hard Sample Prototype Learning -- Brain-Aware Replacements for Supervised Contrastive Learning in Detection of Alzheimer's Disease -- Heart and Lung Imaging -- AANet: Artery-Aware Network for Pulmonary Embolism Detection in CTPA Images -- Siamese Encoder-based Spatial-Temporal Mixer for Growth Trend Prediction of Lung Nodules on CT Scans -- What Makes for Automatic Reconstruction of Pulmonary Segments -- CFDA: Collaborative Feature Disentanglement and Augmentation for Pulmonary Airway Tree Modeling of COVID-19 CTs -- Decoupling Predictions in Distributed Learning for Multi-Center Left Atrial MRI Segmentation -- Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision -- Diffusion Deformable Model for 4D Temporal Medical Image Generation -- SAPJNet: Sequence-Adaptive Prototype-Joint Network for Small Sample Multi-Sequence MRI Diagnosis -- Evolutionary Multi-objective Architecture Search Framework: Application to COVID-19 3D CT Classification -- Detecting Aortic Valve Pathology from the 3-Chamber Cine Cardiac MRI View -- CheXRelNet: An Anatomy-Aware Model for Tracking Longitudinal Relationships between Chest X-Rays -- Reinforcement learning for active modality selection during diagnosis -- Ensembled Prediction of Rheumatic Heart Disease from Ungated Doppler Echocardiography Acquired in Low-Resource Settings -- Attention mechanisms for physiological signal deep learning: which attention should we take? -- Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance -- Multimodal Contrastive Learning for Prospective Personalized Estimation of CT Organ Dose -- RTN: Reinforced Transformer Network for Coronary CT Angiography Vessel-level Image Quality Assessment -- A Comprehensive Study of Modern Architectures and Regularization Approaches on CheXpert5000 -- LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule Detection -- Consistency-based Semi-supervised Evidential Active Learning for Diagnostic Radiograph Classification -- Self-Rating Curriculum Learning for Localization and Segmentation of Tuberculosis on Chest Radiograph -- Rib Suppression in Digital Chest Tomosynthesis -- Multi-Task Lung Nodule Detection in Chest Radiographs with a Dual Head Network -- Dermatology -- Data-Driven Deep Supervision for Skin Lesion Classification -- Out-of-Distribution Detection for Long-tailed and Fine-grained Skin Lesion Images -- FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis -- Reliability-aware Contrastive Self-ensembling for Semi-supervised Medical Image Classification.
520 $a The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022. The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology; Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging; Part III: Breast imaging; colonoscopy; computer aided diagnosis; Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I; Part V: Image segmentation II; integration of imaging with non-imaging biomarkers; Part VI: Image registration; image reconstruction; Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning - domain adaptation and generalization; Part VIII: Machine learning - weakly-supervised learning; machine learning - model interpretation; machine learning - uncertainty; machine learning theory and methodologies.
650 0 $a Diagnostic imaging $x Data processing $v Congresses. $3 893542
650 1 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 890871
650 2 4 $a Computer and Information Systems Applications. $3 3538505
650 2 4 $a Machine Learning. $3 3382522
650 2 4 $a Computers and Education. $3 892757
650 2 4 $a Computer Application in Social and Behavioral Sciences. $3 3538516
650 2 4 $a Biomedical Engineering and Bioengineering. $3 3381533
700 1 $a Wang, Linwei. $3 2103299
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science ; $v 13431. $3 3605666
856 4 0 $u https://doi.org/10.1007/978-3-031-16431-6
950 $a Computer Science (SpringerNature-11645)