07707nam 2200493 450 99649035750331620230227132053.03-031-17979-X(MiAaPQ)EBC7102413(Au-PeEL)EBL7102413(CKB)24950556200041(PPN)264953517(EXLCZ)992495055620004120230227d2022 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierCancer prevention through early detection first international workshop, CaPTion 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings /edited by Sharib Ali [and five others]Cham, Switzerland :Springer,[2022]©20221 online resource (175 pages)Lecture Notes in Computer Science Ser. ;v.13581Print version: Ali, Sharib Cancer Prevention Through Early Detection Cham : Springer,c2022 9783031179785 Includes bibliographical references and index.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.Lecture Notes in Computer Science Ser.Diagnostic imagingData processingCongressesDiagnostic imagingDigital techniquesDiagnostic imagingData processingDiagnostic imagingDigital techniques.616.0754Ali SharibMiAaPQMiAaPQMiAaPQBOOK996490357503316Cancer prevention through early detection3027973UNISA