Medical image computing and computer assisted intervention - MICCAI 2021 : 24th international conference, Strasbourg, France, September 27-October 1, 2021 : proceedings. Part VIII / Marleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert (eds.)
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 542 r...
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| Other Authors: | , , , , , , |
| Other title: | MICCAI 2021. |
| Format: | Conference Proceeding eBook |
| Language: | English |
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Springer,
[2021]
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| Series: | Lecture notes in computer science ;
12908. LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics. |
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Table of 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
- CÂ{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.