Cancer Prevention Through Early Detection

Name: Cancer Prevention Through Early Detection | First International Workshop, CaPTion 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings
Brand: Springer
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First International Workshop, CaPTion 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings

Sharib Ali Fons van der Sommen Bartlomiej Wladyslaw Papiez Maureen van Eijnatten Yueming Jin Iris Kolenbrander(Herausgeber*in)

Springer (Verlag)

Erschienen am 30. September 2022

XI, 170 Seiten

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978-3-031-17979-2 (ISBN)

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Inhalt

Intro
Preface
Organization
Contents
Classification
3D-Morphomics, Morphological Features on CT Scans for Lung Nodule Malignancy Diagnosis
1 Introduction
2 Methods
2.1 Data Sets
2.2 Data Analysis Models
3 Results
3.1 3D-Morphomics
3.2 Lung Nodule Diagnosis Performances of 3D-Morphomics
4 Conclusions
References
.26em plus .1em minus .1emSelf-supervised Approach for a Fully Assistive Esophageal Surveillance: Quality, Anatomy and Neoplasia Guidance
1 Introduction
2 Related Work
3 Method
3.1 Self-supervision Solving Jigsaw Puzzle
3.2 Fine-Tuning with Angular Margin Loss
4 Experiments and Results
4.1 Implementation Details
4.2 Data Collection and Evaluation Metrics
4.3 Comparison with SOTA Methods
4.4 Qualitative Analysis
5 Conclusion
References
Multi-scale Deformable Transformer for the Classification of Gastric Glands: The IMGL Dataset
1 Introduction
2 Related Works
3 Materials and Methods
3.1 IMGL Dataset Description
3.2 The Proposed IMGL-VTNet Architecture
3.3 Multi-scale Deformable Transformer Encoder
4 Experimental Results
4.1 A Comparison of State-of-the-Art Methods: IMGL Dataset
4.2 Feature Map Scales Analysis
4.3 Application of the Proposed Model to Pedestrian Detection
5 Conclusion
References
Parallel Classification of Cells in Thinprep Cytology Test Image for Cervical Cancer Screening
1 Introduction
2 Method
2.1 Overview
2.2 Dual Classifiers in Parallel
2.3 Intra-class Compactness
2.4 Implementation Details
3 Experimental Results
3.1 Datasets
3.2 Classification Performance
3.3 Evolving of the Latent Space
4 Discussion and Conclusion
References
Detection and Diagnosis
Lightweight Transformer Backbone for Medical Object Detection
1 Introduction
2 Methodology
2.1 Overview of Proposed Method
2.2 Feature Map Rearrangement and Reconstruction
2.3 Lightweight Transformer on Feature Patches
3 Experiments and Results
3.1 Dataset and Evaluation Metrics
3.2 Implementation Details
3.3 Experimental Results
4 Conclusion
References
Contrastive and Attention-Based Multiple Instance Learning for the Prediction of Sentinel Lymph Node Status from Histopathologies of Primary Melanoma Tumours
1 Introduction
2 Materials and Methods
2.1 Dataset
2.2 Multiple Instance Learning
2.3 Proposed Model
2.4 Self-supervised Contrastive Learning:
3 Experimental Set-Up and Results
3.1 Feature Extraction
3.2 Experiments
4 Discussion
5 Conclusions
References
Knowledge Distillation with a Class-Aware Loss for Endoscopic Disease Detection
1 Introduction
2 Related Work
3 Materials and Method
3.1 Datasets
3.2 Proposed Knowledge-Distillation Framework
4 Experiments and Results
4.1 Experimental Setup and Evaluation Metrics
4.2 Results
5 Conclusion
References
IF3: An Interpretable Feature Fusion Framework for Lesion Risk Assessment Based on Auto-constructed Fuzzy Cognitive Maps
1 Introduction
2 Methodology
2.1 Fuzzy Cognitive Maps
2.2 Proposed Framework
3 Experiments and Results
3.1 Dataset Description and Parameter Settings
3.2 Interpretable Example of Risk Assessment Using IF3
3.3 Performance Evaluation of IF3
4 Discussion and Conclusions
References
Lesion Characterization
A CAD System for Real-Time Characterization of Neoplasia in Barrett's Esophagus NBI Videos
1 Introduction
2 Methods
2.1 Data
2.2 Network Architecture, Training and Evaluation
2.3 Video Analysis Methods
3 Experimental Results
4 Discussion
5 Conclusions
References
Efficient Out-of-Distribution Detection of Melanoma with Wavelet-Based Normalizing Flows
1 Introduction
2 Background
2.1 Normalizing Flows
2.2 Wavelet Flow
3 Methods
4 Results and Discussion
5 Conclusion
References
Robust Colorectal Polyp Characterization Using a Hybrid Bayesian Neural Network
1 Introduction
2 Methodology
2.1 Dataset
2.2 Bayesian Neural Networks
2.3 Model Architecture
2.4 Evaluation Metrics
3 Results
3.1 Experimental Setting
3.2 Calibration-performance Assessment
3.3 Model Performance Comparison
3.4 Generalization and Robustness to Over-Fitting Assessment
4 Discussion and Conclusion
References
Active Data Enrichment by Learning What to Annotate in Digital Pathology
1 Introduction
2 Methodology
2.1 Annotation Protocol
2.2 Dataset Enrichment
3 Results
3.1 Unsupervised Data Enrichment
3.2 Supervised Active Data Enrichment
4 Conclusion
References
Segmentation, Registration, and Image-Guided Intervention
Comparing Training Strategies Using Multi-Assessor Segmentation Labels for Barrett's Neoplasia Detection
1 Introduction
2 Materials and Methods
2.1 Data Set
2.2 Segmentation Ground-truth Assembly
2.3 Network Architecture
2.4 Training Details
3 Experiments and Results
3.1 Metrics
3.2 Results
4 Discussion and Conclusions
References
Improved Pancreatic Tumor Detection by Utilizing Clinically-Relevant Secondary Features
1 Introduction
2 Related Work on PDAC Detection
3 Methods
3.1 Data Collection
3.2 Segmentation Model for Classification and Localization
3.3 Experiments
3.4 Data Preparation and Training Details
4 Results and Discussion
5 Conclusion
References
Strategising Template-Guided Needle Placement for MR-targeted Prostate Biopsy
1 Introduction
2 Method
2.1 Patient-specific Prostate MR-derived Biopsy Environment
2.2 The MDP Components
2.3 Policy Learning
3 Experiments
4 Results
5 Discussion and Conclusion
References
Semantic-Aware Registration with Weakly-Supervised Learning
1 Introduction
2 Method
2.1 Structural Constraints
2.2 Adaptive Registration
3 Experiments
3.1 Registration Results
4 Conclusion
References
Author Index

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