Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 : 24th International Conference, Strasbourg, France, September 27 - October 1, 2021, Proceedings, Part VIII / edited by Marleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert.

Format:

Book

Contributor:

Bruijne, Marleen de, Editor.

Cattin, Philippe C., Editor.

Cotin, Stéphane, Editor.

Padoy, Nicolas., Editor.

Speidel, Stefanie, Editor.

Zheng, Yefeng., Editor.

Essert, Caroline, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 12908

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12908

Language:

English

Subjects (All):

Computer vision.

Artificial intelligence.

Pattern recognition systems.

Medical informatics.

Computer Vision.

Artificial Intelligence.

Automated Pattern Recognition.

Health Informatics.

Local Subjects:

Computer Vision.

Artificial Intelligence.

Automated Pattern Recognition.

Health Informatics.

Physical Description:

1 online resource (XXXVIII, 704 pages) : 227 illustrations, 213 illustrations in color.

Edition:

1st ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.* The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging - others; and clinical applications - oncology Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound *The conference was held virtually.

Contents:

Clinical Applications - Ophthalmology

Relational Subsets Knowledge Distillation for Long-tailed Retinal Diseases Recognition

Cross-domain Depth Estimation Network for 3D Vessel Reconstruction in OCT Angiography

Distinguishing Differences Matters: Focal Contrastive Network for Peripheral Anterior Synechiae Recognition

RV-GAN: Segmenting Retinal Vascular Structure in Fundus Photographs using a Novel Multi-scale Generative Adversarial Network

MIL-VT: Multiple Instance Learning Enhanced Vision Transformer for Fundus Image Classification

Local-global Dual Perception based Deep Multiple Instance Learning for Retinal Disease Classification

BSDA-Net: A Boundary Shape and Distance Aware Joint Learning Framework for Segmenting and Classifying OCTA Images

LensID: A CNN-RNN-Based Framework Towards Lens Irregularity Detection in Cataract Surgery Videos

I-SECRET: Importance-guided fundus image enhancement via semi-supervised contrastive constraining

Few-shot Transfer Learning for Hereditary Retinal Diseases Recognition

Simultaneous Alignment and Surface Regression Using Hybrid 2D-3D Networks for 3D Coherent Layer Segmentation of Retina OCT Images

Computational (Integrative) Pathology

GQ-GCN: Group Quadratic Graph Convolutional Network for Classification of Histopathological Images

Nuclei Grading of Clear Cell Renal Cell Carcinoma in Histopathological Image by Composite High-Resolution Network

Prototypical models for classifying high-risk atypical breast lesions

Hierarchical Attention Guided Framework for Multi-resolution Collaborative Whole Slide Image Segmentation

Hierarchical Phenotyping and Graph Modeling of Spatial Architecture in Lymphoid Neoplasms

A computational geometry approach for modeling neuronal fiber pathways

TransPath: Transformer-based Self-supervised Learning for Histopathological Image Classification

From Pixel to Whole Slide: Automatic Detection of Microvascular Invasion in Hepatocellular Carcinoma on Histopathological Image via Cascaded Networks

DT-MIL: Deformable Transformer for Multi-instance Learning on Histopathological Image

Early Detection of Liver Fibrosis Using Graph Convolutional Networks

Hierarchical graph pathomic network for progression free survival prediction

Increasing Consistency of Evoked Response in Thalamic Nuclei During Repetitive Burst Stimulation of Peripheral Nerve in Humans

Weakly supervised pan-cancer segmentation tool

Structure-Preserving Multi-Domain Stain Color Augmentation using Style-Transfer with Disentangled Representations

MetaCon: Meta Contrastive Learning for Microsatellite Instability Detection

Generalizing Nucleus Recognition Model in Multi-source Ki67 Immunohistochemistry Stained Images via Domain-specific Pruning

Cells are Actors: Social Network Analysis with Classical ML for SOTA Histology Image Classification

Instance-based Vision Transformer for Subtyping of Papillary Renal Cell Carcinoma in Histopathological Image

Hybrid Supervision Learning for Whole Slide Image Classification

MorphSet: Improving Renal Histopathology Case Assessment Through Learned Prognostic Vectors

Accounting for Dependencies in Deep Learning based Multiple Instance Learning for Whole Slide Imaging

Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks

Pay Attention with Focus: A Novel Learning Scheme for Classification of Whole Slide Images

Modalities - Microscopy

Developmental Stage Classification of Embryos Using Two-Stream Neural Network with Linear-Chain Conditional Random Field

Semi-supervised Cell Detection in Time-lapse Images Using Temporal Consistency

Cell Detection in Domain Shift Problem Using Pseudo-Cell-Position Heatmap

2D Histology Meets 3D Topology: Cytoarchitectonic Brain Mapping with Graph Neural Networks

Annotation-efficient Cell Counting

A Deep Learning Bidirectional Temporal Tracking Algorithm for Automated Blood Cell Counting from Non-invasive Capillaroscopy Videos

Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification

Learning Neuron Stitching for Connectomics

CA^{2.5}-Net Nuclei Segmentation Framework with a Microscopy Cell Benchmark Collection

Automated Malaria Cells Detection from Blood Smears under Severe Class Imbalance via Importance-aware Balanced Group Softmax

Non-parametric vignetting correction for sparse spatial transcriptomics images

Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy

Deep Reinforcement Exemplar Learning for Annotation Refinement

Modalities - Histopathology

Instance-aware Feature Alignment for Cross-domain Cell Nuclei Detection in Histopathology Images

Positive-unlabeled Learning for Cell Detection in Histopathology Images with Incomplete Annotations

GloFlow: Whole Slide Image Stitching from Video using Optical Flow and Global Image Alignment

Multi-modal Multi-instance Learning using Weakly Correlated Histopathological Images and Tabular Clinical Information

Ranking loss: A ranking-based deep neural network for colorectal cancer grading in pathology images

Spatial Attention-based Deep Learning System for Breast Cancer Pathological Complete Response Prediction with Serial Histopathology Images in Multiple Stains

Integration of Patch Features through Self-Supervised Learning and Transformer for Survival Analysis on Whole Slide Images

Contrastive Learning Based Stain Normalization Across Multiple Tumor Histopathology

Semi-supervised Adversarial Learning for Stain Normalisation in Histopathology Images

Learning Visual Features by Colorization for Slide-Consistent Survival Prediction from Whole Slide Images

Adversarial learning of cancer tissue representations

A Multi-attribute Controllable Generative Model for Histopathology Image Synthesis

Modalities - Ultrasound

USCL: Pretraining Deep Ultrasound Image Diagnosis Model through Video Contrastive Representation Learning

Identifying Quantitative and Explanatory Tumor Indexes from Dynamic Contrast Enhanced Ultrasound

Weakly-Supervised Ultrasound Video Segmentation with Minimal Annotations

Content-Preserving Unpaired Translation from Simulated to Realistic Ultrasound Images

Visual-Assisted Probe Movement Guidance for Obstetric Ultrasound Scanning using Landmark Retrieval

Training Deep Networks for Prostate Cancer Diagnosis Using Coarse Histopathological Labels

Rethinking Ultrasound Augmentation: A Physics-Inspired Approach.

Other Format:

Printed edition:

ISBN:

978-3-030-87237-3

9783030872373

Access Restriction:

Restricted for use by site license.