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MARC Lista (tabellare)
Applications of medical artificial intelligence : first international workshop, AMAI 2022, held in conjunction with MICCAI 2022, Singapore, September 18, 2022, proceedings / / edited by Shandong Wu, Behrouz Shabestari, and Lei Xing
Applications of medical artificial intelligence : first international workshop, AMAI 2022, held in conjunction with MICCAI 2022, Singapore, September 18, 2022, proceedings / / edited by Shandong Wu, Behrouz Shabestari, and Lei Xing
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (171 pages)
Disciplina 006.3
Collana Lecture Notes in Computer Science Ser.
Soggetto topico Artificial intelligence - Medical applications
Diagnostic imaging - Data processing
ISBN 3-031-17721-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Increasing the Accessibility of Peripheral Artery Disease Screening with Deep Learning -- 1 Problem -- 2 Related Work -- 3 Data Collection Study -- 4 System Development -- 5 Validation Study -- 6 Conclusion -- References -- Deep Learning Meets Computational Fluid Dynamics to Assess CAD in CCTA -- 1 Introduction -- 2 Automated Assessment of CAD in CCTA -- 2.1 Straightened Representation of the Coronary Vessels -- 2.2 Representing Ground-Truth Segmentation as a 3D Mesh -- 2.3 Segmentation of Vessels Using U-Nets in Upsampled CTTA -- 2.4 Blood Flow Simulation -- 3 Experimental Validation -- 4 Conclusions and Future Work -- References -- Machine Learning for Dynamically Predicting the Onset of Renal Replacement Therapy in Chronic Kidney Disease Patients Using Claims Data -- 1 Introduction -- 2 Methods -- 2.1 Dataset Description -- 2.2 Task Definition -- 2.3 Data Representation and Processing -- 2.4 Model Description -- 2.5 Model Evaluation -- 3 Experiments and Results -- 3.1 Study Population and Dataset -- 3.2 Model Performance -- 4 Conclusions -- References -- Uncertainty-Aware Geographic Atrophy Progression Prediction from Fundus Autofluorescence -- 1 Introduction -- 2 Method -- 2.1 Data -- 2.2 Model Development -- 2.3 Uncertainty Estimation Using Deep Ensemble -- 3 Results -- 4 Conclusions -- References -- Automated Assessment of Renal Calculi in Serial Computed Tomography Scans -- 1 Introduction -- 1.1 Our Contributions -- 2 Materials and Methods -- 2.1 Data -- 2.2 Calculi Detection and Segmentation -- 2.3 Registration and Stone Matching -- 2.4 Manual Review and Tracking -- 2.5 Evaluation of Performance -- 2.6 Statistical Analysis -- 3 Results -- 3.1 Cohort Characteristics -- 3.2 Performance of the Stone Detection and Segmentation -- 3.3 Performance of Stone Tracking -- 4 Discussion -- References.
Prediction of Mandibular ORN Incidence from 3D Radiation Dose Distribution Maps Using Deep Learning -- 1 Introduction -- 2 Methods and Materials -- 2.1 Data -- 2.2 Prediction Models -- 2.3 Model Evaluation -- 2.4 Statistical Analysis -- 3 Results -- 4 Discussion -- 4.1 ORN Prediction -- 4.2 Study Limitations and Future Work -- 5 Conclusion -- References -- Analysis of Potential Biases on Mammography Datasets for Deep Learning Model Development -- 1 Introduction -- 2 Materials and Methods -- 2.1 Mammography Dataset -- 2.2 Bias Analysis -- 2.3 Bias Correction Techniques -- 2.4 Experimental Setup -- 3 Results and Discussion -- 4 Conclusions -- References -- ECG-ATK-GAN: Robustness Against Adversarial Attacks on ECGs Using Conditional Generative Adversarial Networks -- 1 Introduction -- 2 Methodology -- 2.1 Generator and Discriminator -- 2.2 Objective Function and Individual Losses -- 2.3 Adversarial Attacks -- 3 Experiments -- 3.1 Data Set Preparation -- 3.2 Hyper-parameters -- 3.3 Quantitative Evaluation -- 3.4 Qualitative Evaluation -- 4 Conclusions and Future Work -- References -- CADIA: A Success Story in Breast Cancer Diagnosis with Digital Pathology and AI Image Analysis -- 1 Introduction -- 2 Methods -- 2.1 Starting Point Analysis and Functional Requirement Collection -- 2.2 Sample Selection and Collection -- 2.3 Digital Image Annotation -- 2.4 Model Development -- 2.5 Model Deployment and Integration -- 3 Results -- 4 Conclusions and Future Perspectives -- References -- Was that so Hard? Estimating Human Classification Difficulty -- 1 Introduction -- 2 Estimating Image Difficulty -- 3 Datasets -- 4 Experiments -- 5 Results -- 6 Discussion and Conclusion -- References -- A Deep Learning-Based Interactive Medical Image Segmentation Framework -- 1 Introduction -- 2 Related Work -- 3 Applicative Scope -- 4 Methodology -- 4.1 System.
4.2 Training with Dynamic Data Generation -- 5 Experimental Results -- 5.1 Setup -- 5.2 Automated Evaluation -- 5.3 User Evaluation -- 6 Conclusion -- References -- Deep Neural Network Pruning for Nuclei Instance Segmentation in Hematoxylin and Eosin-Stained Histological Images -- 1 Introduction -- 2 Method -- 2.1 Datasets -- 2.2 Segmentation and Regression Models -- 2.3 Pruning -- 2.4 Merging and Post-processing -- 2.5 Evaluation Metrics -- 3 Results and Discussion -- 4 Conclusion -- References -- Spatial Feature Conservation Networks (SFCNs) for Dilated Convolutions to Improve Breast Cancer Segmentation from DCE-MRI -- 1 Introduction -- 2 Methods -- 2.1 Compensation Module -- 2.2 Network Architecture -- 2.3 Performance Evaluation -- 2.4 Image Dataset and Data Preparation -- 3 Results -- 4 Discussion and Conclusion -- References -- The Impact of Using Voxel-Level Segmentation Metrics on Evaluating Multifocal Prostate Cancer Localisation -- 1 Introduction -- 2 Materials and Methods -- 2.1 Prostate Lesion Segmentation for Procedure Planning -- 2.2 Voxel-Level Segmentation Metrics -- 2.3 Lesion-Level Object Detection Metrics -- 2.4 Lesion Detection Metrics for Multifocal Segmentation Output -- 2.5 Correlation, Pairwise Agreement and Impact on Evaluation -- 3 Results -- 3.1 Comparison Between DSC and HD -- 3.2 Comparison Between Voxel- and Lesion-Level Metrics -- 4 Conclusion -- References -- OOOE: Only-One-Object-Exists Assumption to Find Very Small Objects in Chest Radiographs -- 1 Introduction -- 2 Methods -- 2.1 Feature Extractor -- 2.2 Point Detection Head -- 3 Experiments -- 3.1 Datasets -- 3.2 Evaluation Metrics -- 3.3 Implementation Details -- 3.4 Comparison to Other Methods -- 3.5 A Closer Look at ET-tube vs. T-tube Detection Performance -- 4 Conclusion -- References -- Wavelet Guided 3D Deep Model to Improve Dental Microfracture Detection.
1 Introduction -- 2 Materials -- 3 Methods -- 4 Results and Discussion -- References -- Author Index.
Record Nr. UNISA-996490357403316
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Artificial intelligence over infrared images for medical applications and medical image assisted biomarker discovery : first MICCAI workshop, AIIIMA 2022, and first MICCAI workshop, MIABID 2022, held in conjunction with MICCAI 2022, Singapore, September 18 and 22, 2022, proceedings / / Siva Teja Kakileti [and nine others] (editors)
Artificial intelligence over infrared images for medical applications and medical image assisted biomarker discovery : first MICCAI workshop, AIIIMA 2022, and first MICCAI workshop, MIABID 2022, held in conjunction with MICCAI 2022, Singapore, September 18 and 22, 2022, proceedings / / Siva Teja Kakileti [and nine others] (editors)
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (200 pages)
Disciplina 610.28563
Collana Lecture notes in computer science
Soggetto topico Artificial intelligence - Medical applications
Diagnostic imaging - Data processing
ISBN 3-031-19660-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface AIIIMA 2022 -- Preface MIABID 2022 -- Organization -- Contents -- Artificial Intelligence over Infrared Images for Medical Applications -- Thermal Radiomics for Improving the Interpretability of Breast Cancer Detection from Thermal Images -- 1 Introduction -- 2 Methodology -- 2.1 Thermal Radiomics -- 2.2 Classification -- 3 Experimentation and Results -- 4 Conclusions -- References -- Radiomics for Breast IR-Imaging Classification -- 1 Introduction -- 2 Breast IR Classification in the Literature -- 3 Dataset Description -- 4 Region of Interest Segmentation -- 5 Radiomic Feature Extraction -- 6 Classification Methodology -- 7 Experiments and Results -- 8 Conclusion -- References -- Early Thermographic Screening of Breast Abnormality in Women with Dense Breast by Thermal, Fractal, and Statistical Analysis -- 1 Background -- 2 Methods -- 3 Results -- 3.1 Thermal Feature-Based Analysis -- 3.2 Fractal Feature-Based Analysis -- 3.3 Statistical Feature-Based Analysis -- 4 Discussion -- 5 Conclusion and Futurescope -- References -- A Novel Thermography-Based Artificial Intelligence-Powered Solution for Screening Breast Cancer -- 1 Introduction -- 1.1 Thermography -- 1.2 Related Work -- 1.3 AI-Powered Breast Cancer Prediction Tool by AI Talos -- 2 Materials and Methods -- 2.1 Dataset Description -- 2.2 CNN Methodology -- 3 Experimental Results -- 4 Conclusion -- References -- Thermographic Toothache Screening by Artificial Intelligence -- 1 Introduction, Review and Objectives -- 2 Materials and Methods -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Non-fever COVID-19 Detection by Infrared Imaging -- 1 Introduction -- 2 Materials and Methods -- 2.1 Infrared Camera Calibration and Precision Assessment -- 2.2 Standard Data Bank Construction (Phase 1) -- 2.3 Classification Algorithm -- 2.4 Prospective Study (Phase 2).
2.5 Statistical Analysis -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Automated Thermal Screening for COVID-19 Using Machine Learning -- 1 Introduction -- 2 Dataset -- 2.1 Thermal Surveillance Dataset -- 2.2 Augmented Surveillance Dataset -- 2.3 Lighting Dataset -- 3 Methodology -- 3.1 Image Preprocessing -- 3.2 Face Detection -- 3.3 Fever Detection -- 3.4 Mask Classification -- 4 Experiments and Results -- 4.1 Face Detection -- 4.2 Mask Classification -- 5 Conclusion -- References -- An Automated Approach for Screening COVID-19 from Thermal Images Using Convolutional Neural Network -- 1 Introduction -- 2 Dataset -- 3 Methodology -- 3.1 Overview -- 3.2 YOLOv5 as Mask Detection Module -- 3.3 Fever Detection Module -- 4 Results and Discussion -- 5 Conclusion -- References -- Infrared Technology for Vascular Abnormality in Finding of Abdominal Aortic Aneurysm -- 1 Introduction -- 1.1 Objective -- 2 Methodology -- 2.1 Model Setup -- 2.2 Boundary Conditions -- 2.3 Physical and Thermal Properties -- 3 Verification Studies for FSI Analysis -- 4 Result and Discussions -- 4.1 Transient FSI Analysis -- 5 Limitations -- 6 Conclusion -- References -- Non-invasive Thermal Imaging for Estimation of the Fecundity of Live Female Onchocerca Worms -- 1 Introduction -- 2 Dataset Description -- 2.1 Study Site and Population -- 2.2 Imaging Protocol -- 2.3 Histopathology and Ground truth -- 3 Methodology -- 3.1 Data Pre-processing -- 3.2 Feature Extraction -- 3.3 Classification -- 4 Experiments and Results -- 5 Conclusion -- References -- Medical Image Assisted Biomarker Discovery -- Counterfactual Image Synthesis for Discovery of Personalized Predictive Image Markers -- 1 Introduction -- 2 Methods -- 3 Experiments and Results -- 3.1 Dataset and Implementation Details -- 3.2 Evaluating Counterfactuals and Discovered Image-Based Markers.
3.3 Counterfactual Results -- 4 Conclusions -- References -- CoRe: An Automated Pipeline for the Prediction of Liver Resection Complexity from Preoperative CT Scans -- 1 Introduction -- 2 Methods -- 2.1 Liver, Lesion, and Vessel Segmentation -- 2.2 Topological Analysis of the Liver Vasculature -- 2.3 Quantitative Imaging Biomarkers for LR Complexity Prediction -- 3 Experiments -- 3.1 Datasets and Preprocessing -- 3.2 Training, Evaluation, and Inference -- 4 Results -- 4.1 Quantitative Results -- 4.2 Qualitative Results -- 5 Discussion and Conclusion -- References -- Diffusion Tensor Imaging Biomarkers for Parkinson's Disease Symptomatology -- 1 Introduction -- 1.1 Voxel-Based Diffusion Analysis and Voxel-Based Diktiometry -- 2 Materials and Methods -- 2.1 Patient Images and Clinical Scores -- 2.2 Preprocessing -- 2.3 Convolutional Neural Network -- 2.4 Diffusion Measures, Sensitivity Maps, and Statistical Processing -- 3 Results and Discussion -- 4 Conclusion -- References -- Prediction of Immune and Stromal Cell Population Abundance from Hepatocellular Carcinoma Whole Slide Images Using Weakly Supervised Learning -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Gene Expression Processing -- 2.3 Image Preprocessing -- 2.4 Deep Learning Models -- 2.5 Attention Map Generation and Statistical Analysis -- 2.6 Inflammatory Cell Density Map Generation -- 3 Results -- 3.1 Unsupervised Hierarchical Clustering of Samples -- 3.2 Evaluation of Deep Learning Models for the Prediction of Activation of Cell Populations -- 3.3 Interpretability and Relationships with Immunotherapy-Related Gene Signatures and with Inflammatory Cells -- 4 Discussion and Conclusion -- References -- Enhancing Local Context of Histology Features in Vision Transformers -- 1 Introduction -- 2 Methods -- 3 Experiments -- 4 Conclusion -- References.
DCIS AI-TIL: Ductal Carcinoma In Situ Tumour Infiltrating Lymphocyte Scoring Using Artificial Intelligence -- 1 Introduction -- 2 Materials -- 3 Methodology -- 3.1 Cell Detection, Cell Classification and Hotspot Analysis -- 3.2 DCIS Segmentation Using GAN -- 3.3 Stromal TIL Scoring Using Artificial Intelligence -- 3.4 Statistical Analysis -- 4 Results and Discussion -- References -- Predictive Biomarkers in Melanoma: Detection of BRAF Mutation Using Dermoscopy -- 1 Introduction -- 2 Methodology -- 2.1 Pre-training Phase -- 2.2 BRAF Classification -- 3 Experimental Setup -- 3.1 Dataset and Evaluation Metrics -- 3.2 Experimental Challenges -- 3.3 Network Training and Computational Environment -- 4 Results and Discussion -- 5 Conclusion -- References -- Author Index.
Record Nr. UNISA-996500063103316
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Biomedical image registration, domain generalisation and out-of-distribution analysis : MICCAI 2021 Challenges, MIDOG 2021, MOOD 2021, and Learn2Reg 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27-October 1, 2021, proceedings / / Marc Aubreville, David Zimmerer, Mattias P. Heinrich, editors
Biomedical image registration, domain generalisation and out-of-distribution analysis : MICCAI 2021 Challenges, MIDOG 2021, MOOD 2021, and Learn2Reg 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27-October 1, 2021, proceedings / / Marc Aubreville, David Zimmerer, Mattias P. Heinrich, editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (201 pages)
Disciplina 616.07540285
Collana Lecture notes in computer science
Soggetto topico Diagnostic imaging - Data processing
ISBN 3-030-97281-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996464536003316
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Biomedical imaging : principles of radiography, tomography and medical physics / / Tim Salditt, Timo Aspelmeier, Sebastian Aeffner
Biomedical imaging : principles of radiography, tomography and medical physics / / Tim Salditt, Timo Aspelmeier, Sebastian Aeffner
Autore Salditt Tim
Pubbl/distr/stampa Berlin, [Germany] ; ; Boston, [Massachusetts] : , : De Gruyter, , 2017
Descrizione fisica 1 online resource (348 pages) : illustrations, tables
Disciplina 616.07/54
Collana De Gruyter Graduate
Soggetto topico Diagnostic imaging - Methodology
Diagnostic imaging - Data processing
Biomedical engineering - Mathematical models
Medical physics
Soggetto genere / forma Electronic books.
ISBN 3-11-042351-0
3-11-042669-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Contents -- Preface and acknowledgements -- 1. Introduction -- 2. Digital image processing -- 3. Essentials of medical x-ray physics -- 4. Tomography -- 5. Radiobiology, radiotherapy, and radiation protection -- 6. Phase contrast radiography -- 7. Object reconstruction: nonideal conditions and noise -- Index
Record Nr. UNINA-9910467062203321
Salditt Tim  
Berlin, [Germany] ; ; Boston, [Massachusetts] : , : De Gruyter, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Biomedical imaging : principles of radiography, tomography and medical physics / / Tim Salditt, Timo Aspelmeier, Sebastian Aeffner
Biomedical imaging : principles of radiography, tomography and medical physics / / Tim Salditt, Timo Aspelmeier, Sebastian Aeffner
Autore Salditt Tim
Pubbl/distr/stampa Berlin, [Germany] ; ; Boston, [Massachusetts] : , : De Gruyter, , 2017
Descrizione fisica 1 online resource (348 pages) : illustrations, tables
Disciplina 616.07/54
Collana De Gruyter Graduate
Soggetto topico Diagnostic imaging - Methodology
Diagnostic imaging - Data processing
Biomedical engineering - Mathematical models
Medical physics
ISBN 3-11-042351-0
3-11-042669-2
Classificazione SCI055000MED003070COM021030MED080000COM018000MAT003000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Contents -- Preface and acknowledgements -- 1. Introduction -- 2. Digital image processing -- 3. Essentials of medical x-ray physics -- 4. Tomography -- 5. Radiobiology, radiotherapy, and radiation protection -- 6. Phase contrast radiography -- 7. Object reconstruction: nonideal conditions and noise -- Index
Record Nr. UNINA-9910795493003321
Salditt Tim  
Berlin, [Germany] ; ; Boston, [Massachusetts] : , : De Gruyter, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Biomedical imaging : principles of radiography, tomography and medical physics / / Tim Salditt, Timo Aspelmeier, Sebastian Aeffner
Biomedical imaging : principles of radiography, tomography and medical physics / / Tim Salditt, Timo Aspelmeier, Sebastian Aeffner
Autore Salditt Tim
Pubbl/distr/stampa Berlin, [Germany] ; ; Boston, [Massachusetts] : , : De Gruyter, , 2017
Descrizione fisica 1 online resource (348 pages) : illustrations, tables
Disciplina 616.07/54
Collana De Gruyter Graduate
Soggetto topico Diagnostic imaging - Methodology
Diagnostic imaging - Data processing
Biomedical engineering - Mathematical models
Medical physics
ISBN 3-11-042351-0
3-11-042669-2
Classificazione SCI055000MED003070COM021030MED080000COM018000MAT003000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Contents -- Preface and acknowledgements -- 1. Introduction -- 2. Digital image processing -- 3. Essentials of medical x-ray physics -- 4. Tomography -- 5. Radiobiology, radiotherapy, and radiation protection -- 6. Phase contrast radiography -- 7. Object reconstruction: nonideal conditions and noise -- Index
Record Nr. UNINA-9910811882503321
Salditt Tim  
Berlin, [Germany] ; ; Boston, [Massachusetts] : , : De Gruyter, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Brainlesion . Part II : glioma, multiple sclerosis, stroke and traumatic brain injuries : 4th international workshop, BrainLes 2018, held in conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, revised selected papers. / / Alessandro Crimi and Spyridon Bakas, editors
Brainlesion . Part II : glioma, multiple sclerosis, stroke and traumatic brain injuries : 4th international workshop, BrainLes 2018, held in conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, revised selected papers. / / Alessandro Crimi and Spyridon Bakas, editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022]
Descrizione fisica 1 online resource (617 pages)
Disciplina 616.99481
Collana Lecture notes in computer science
Soggetto topico Brain - Wounds and injuries
Diagnostic imaging - Data processing
Brain - Tumors
ISBN 3-031-09002-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996483162803316
Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Cancer 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]
Cancer 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]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (175 pages)
Disciplina 616.0754
Collana Lecture Notes in Computer Science Ser.
Soggetto topico Diagnostic imaging - Data processing
Diagnostic imaging - Digital techniques
ISBN 3-031-17979-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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.
Record Nr. UNISA-996490357503316
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Clinical image-based procedures, distributed and collaborative learning, artificial intelligence for combating COVID-19 and secure and privacy-preserving machine learning : 10th Workshop, CLIP 2021, Second Workshop, DCL 2021, First Workshop, LL-COVID19 2021, and First Workshop and Tutorial, PPML 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, proceedings / / Cristina Oyarzun Laura [and three others] editors
Clinical image-based procedures, distributed and collaborative learning, artificial intelligence for combating COVID-19 and secure and privacy-preserving machine learning : 10th Workshop, CLIP 2021, Second Workshop, DCL 2021, First Workshop, LL-COVID19 2021, and First Workshop and Tutorial, PPML 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, proceedings / / Cristina Oyarzun Laura [and three others] editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (201 pages)
Disciplina 616.07540285
Collana Lecture Notes in Computer Science
Soggetto topico Diagnostic imaging - Data processing
Artificial intelligence - Medical applications
ISBN 3-030-90874-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Additional Editors -- CLIP Preface -- CLIP Organization -- DCL Preface -- DCL Organization -- LL-COVID-19 Preface -- LL-COVID-19 Organization -- PPML Preface -- PPML Organization -- Contents -- CLIP -- Intestine Segmentation with Small Computational Cost for Diagnosis Assistance of Ileus and Intestinal Obstruction -- 1 Introduction -- 2 Methods -- 2.1 Overview -- 2.2 Distance Map Estimation for Preventing Incorrect Shortcuts -- 2.3 Graph-Based Segmentation and Visualization -- 3 Experimental Results -- 3.1 Experimental Setup -- 3.2 Evaluations -- 4 Discussion -- 5 Conclusions -- References -- Generation of Patient-Specific, Ligamentoskeletal, Finite Element Meshes for Scoliosis Correction Planning -- 1 Introduction -- 2 Methods -- 2.1 Overview -- 2.2 Patient-Specific, Ligamentoskeletal, Finite Element Mesh Generation -- 3 Results -- 3.1 Datasets -- 3.2 Quantitative Results -- 3.3 Qualitative Results -- 4 Conclusion -- References -- Bayesian Graph Neural Networks for EEG-Based Emotion Recognition -- 1 Introduction -- 2 Methods -- 2.1 Bayesian Graph Neural Networks -- 2.2 Sparse Graph Variational Auto-encoder -- 2.3 Algorithm for BGNN -- 3 Experiments -- 3.1 Datasets -- 3.2 Classification Settings -- 3.3 Results -- 4 Discussion -- 4.1 Ablation Study -- 4.2 Latent Communities -- 5 Conclusions -- References -- ViTBIS: Vision Transformer for Biomedical Image Segmentation -- 1 Introduction -- 2 Related Work -- 2.1 Convolutional Neural Network -- 2.2 Attention Mechanism -- 2.3 Transformers -- 2.4 Background -- 3 Method -- 3.1 Dataset -- 3.2 Network Architecture -- 3.3 Residual Connection -- 3.4 Loss Function -- 3.5 Evaluation Metrics -- 3.6 Implementation Details -- 4 Results -- 4.1 Ablation Studies -- 5 Conclusions -- References -- Attention-Guided Pancreatic Duct Segmentation from Abdominal CT Volumes -- 1 Introduction -- 2 Methods.
2.1 Pancreatic Attention-Guide -- 2.2 Multi-scale Aggregation -- 3 Experiments and Results -- 3.1 Dataset and Settings -- 3.2 Segmentation Results and Discussion -- 4 Conclusion -- References -- Development of the Next Generation Hand-Held Doppler with Waveform Phasicity Predictive Capabilities Using Deep Learning -- 1 Introduction -- 1.1 Background -- 1.2 Innovation -- 1.3 Implementation Summary -- 2 Methods -- 2.1 Data Preparation -- 2.2 Model Development -- 2.3 Hardware Platform -- 3 Results -- 3.1 Baseline Validation -- 3.2 Manual Experiment -- 4 Conclusion -- References -- Learning from Mistakes: An Error-Driven Mechanism to Improve Segmentation Performance Based on Expert Feedback -- 1 Introduction -- 2 Data -- 3 Method -- 4 Experiments and Results -- 4.1 Proof of Concept: Recovering Systematic Errors -- 4.2 Clinical Application: Predicting Expert Corrections -- 5 Discussion and Conclusion -- References -- TMJOAI: An Artificial Web-Based Intelligence Tool for Early Diagnosis of the Temporomandibular Joint Osteoarthritis -- 1 Introduction -- 2 Dataset -- 3 Proposed Methods -- 3.1 Feature Selection -- 3.2 Comparison of Multiple Machine Learning Algorithms -- 3.3 Histogram Matching -- 4 Experimental Results -- 4.1 Experiments -- 4.2 Algorithm Comparison Results -- 4.3 Histogram Matching and Mandibular Fossa Features Results -- 4.4 Deployment -- 5 Conclusion -- References -- COVID-19 Infection Segmentation from Chest CT Images Based on Scale Uncertainty -- 1 Introduction -- 2 Method -- 2.1 Infection Region Segmentation by ISNet -- 2.2 Scale Uncertainty-Aware Prediction Aggregation -- 3 Experiments and Results -- 3.1 Ablation and Comparative Study of ISNet -- 3.2 Segmentation by Aggregation FCN -- 4 Discussion and Conclusions -- References -- DCL -- Multi-task Federated Learning for Heterogeneous Pancreas Segmentation -- 1 Introduction -- 2 Methods.
2.1 FedAvg -- 2.2 FedProx -- 2.3 Dynamic Task Prioritization -- 2.4 Dynamic Weight Averaging -- 3 Experiments and Results -- 3.1 Datasets -- 3.2 Experimental Details -- 3.3 Results -- 4 Discussion -- 5 Conclusion -- References -- Federated Learning in the Cloud for Analysis of Medical Images - Experience with Open Source Frameworks -- 1 Introduction -- 2 Related Work -- 3 Dataset Used in Evaluation -- 4 Overview of Available Open Source Frameworks for FL -- 4.1 TensorFlow Federated -- 4.2 PySyft -- 4.3 Flower -- 5 Experiment Setup -- 6 Results -- 6.1 Results for EfficientNetB0 Architecture -- 6.2 Results for ResNet50 Architecture -- 7 Conclusion -- References -- On the Fairness of Swarm Learning in Skin Lesion Classification -- 1 Introduction -- 2 Related Works -- 2.1 Collaborative Learning and Their Application on Healthcare -- 2.2 Security and Privacy of Federated Learning -- 2.3 Fairness -- 3 Problem Setting and Methods -- 3.1 Problem Setting -- 3.2 Swarm Learning -- 3.3 Local and Centralized Training -- 3.4 Fairness Definition and Metrics -- 4 Experiment and Results -- 4.1 Dataset -- 4.2 Implementation Details -- 4.3 Biases in Models Trained with Different Strategies -- 5 Discussion and Conclusion -- References -- LL-COVID19 -- Lessons Learned from the Development and Application of Medical Imaging-Based AI Technologies for Combating COVID-19: Why Discuss, What Next -- 1 Introduction -- 2 Data Definition -- 3 Data Availability -- 4 Translational Research -- 5 Summary and Next Steps -- References -- The Role of Pleura and Adipose in Lung Ultrasound AI -- 1 Introduction -- 2 Methodology -- 2.1 SubQ Masking -- 2.2 Data -- 2.3 Architecture -- 2.4 Training Strategy -- 3 Experiments -- 4 Results and Discussions -- 5 Conclusion -- References -- DuCN: Dual-Children Network for Medical Diagnosis and Similar Case Recommendation Towards COVID-19.
1 Introduction -- 2 Method -- 2.1 Proposed Model -- 2.2 Dual-Children Network -- 2.3 Loss Functions -- 3 Experiments and Results -- 3.1 Dataset and Experiments -- 3.2 Results -- 3.3 Ablation Study -- 4 Discussion and Conclusions -- References -- PPML -- Data Imputation and Reconstruction of Distributed Parkinson's Disease Clinical Assessments: A Comparative Evaluation of Two Aggregation Algorithms -- 1 Introduction -- 1.1 Clinical Assessments and Challenges -- 1.2 Contributions -- 2 Related Work -- 3 Methods -- 3.1 Data -- 3.2 Model Setup -- 3.3 Aggregation Algorithms -- 4 Experimental Results -- 4.1 Effect of Number of Missing Modalities During Training -- 4.2 Effect of Number of Missing Values During Evaluation -- 5 Discussion and Conclusion -- References -- Defending Medical Image Diagnostics Against Privacy Attacks Using Generative Methods: Application to Retinal Diagnostics -- 1 Introduction -- 2 Background -- 3 Prior Work -- 4 Methodology -- 4.1 Threat Model -- 4.2 Approach for Data Producer to Defend Privacy -- 4.3 Novel Metric Balancing Utility and Privacy -- 5 Experiments -- 5.1 Dataset -- 5.2 Results -- 6 Discussion and Limitations -- 7 Conclusion -- References -- Author Index.
Record Nr. UNISA-996464421703316
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
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Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging : 12th International Workshop, CLIP 2023 1st International Workshop, FAIMI 2023 and 2nd International Workshop, EPIMI 2023 Vancouver, BC, Canada, October 8 and October 12, 2023 Proceedings / / Stefan Wesarg [and nine others], editors
Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging : 12th International Workshop, CLIP 2023 1st International Workshop, FAIMI 2023 and 2nd International Workshop, EPIMI 2023 Vancouver, BC, Canada, October 8 and October 12, 2023 Proceedings / / Stefan Wesarg [and nine others], editors
Edizione [First edition.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, Springer Nature Switzerland AG, , [2023]
Descrizione fisica 1 online resource (327 pages)
Disciplina 610.28563
Collana Lecture Notes in Computer Science Series
Soggetto topico Artificial intelligence - Medical applications
Diagnostic imaging
Diagnostic imaging - Data processing
ISBN 3-031-45249-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Additional Editors -- CLIP Preface -- CLIP Organization -- FAIMI Preface -- FAIMI Organization -- EPIMI Preface -- EPIMI Organization -- Contents -- CLIP -- Automated Hand Joint Classification of Psoriatic Arthritis Patients Using Routinely Acquired Near Infrared Fluorescence Optical Imaging -- 1 Introduction -- 2 Background -- 3 Method -- 4 Results -- 5 Discussion and Future Work -- References -- Automatic Neurocranial Landmarks Detection from Visible Facial Landmarks Leveraging 3D Head Priors -- 1 Introduction -- 2 Methods -- 2.1 Datasets and Preprocessing -- 2.2 Models Training and Evaluation -- 3 Experimental Results -- 3.1 Neurocranial Landmark Coordinates Prediction -- 3.2 3DMM Validation -- 3.3 Ablation Study -- 4 Discussion and Conclusions -- References -- Subject-Specific Modelling of Knee Joint Motion for Routine Pre-operative Planning -- 1 Introduction -- 2 Method -- 2.1 Contact Surface Model of PF and TF Joint -- 2.2 Computation of Knee Flexion Angle -- 2.3 Matching Tibia and Patella Poses -- 3 Experiments and Discussions -- 3.1 Evaluation of Generated Patella and Tibia Poses -- 3.2 Evaluation of Tibia and Patella Pose Matching -- 4 Conclusion -- References -- Towards Fine-Grained Polyp Segmentation and Classification -- 1 Introduction -- 2 Method -- 2.1 Swin Transformer Encoder -- 2.2 Multi-Scale Feature Enhancement -- 2.3 Patch-Expanding Decoder -- 2.4 Upsample Head -- 2.5 Loss Function -- 3 PolypSegm-ASH Dataset -- 4 Results -- 4.1 Experiments on PolypSegm-ASH -- 4.2 Experiments on Binary Polyp Segmentation -- 4.3 Ablation Study. Effect of Up-Samples Before Predictions -- 5 Conclusion -- References -- Automated Orientation and Registration of Cone-Beam Computed Tomography Scans -- 1 Introduction -- 2 Materials -- 3 Proposed Method -- 3.1 Automated Standardized Orientation (ASO) -- 3.2 Automated Registration (AReg).
3.3 Evaluation Metrics -- 3.4 Implementation -- 4 Results -- 4.1 Orientation -- 4.2 Registration -- 5 Discussion -- 6 Conclusion -- A Appendix -- References -- Deep Learning-Based Fast MRI Reconstruction: Improving Generalization for Clinical Translation -- 1 Introduction -- 2 Methods -- 2.1 Background -- 2.2 Physically-Primed DNN for MRI Reconstruction -- 3 Experiments -- 3.1 Dataset -- 3.2 Experimental Methodology -- 3.3 Results -- 4 Conclusions -- References -- Uncertainty Based Border-Aware Segmentation Network for Deep Caries -- 1 Introduction -- 2 Related Work -- 2.1 Dental Caries Image Segmentation -- 2.2 Uncertainty Quantification -- 3 Method -- 3.1 Border-Aware Network Using SDF -- 3.2 Uncertainty Based Caries Segmentation -- 4 Experiments and Discussion -- 4.1 Dataset and Settings -- 4.2 Verification of SDF Effectiveness -- 4.3 Verification of Model Robustness -- 5 Conclusion -- References -- An Efficient and Accurate Neural Network Tool for Finding Correlation Between Gene Expression and Histological Images -- 1 Introduction -- 2 Methodology -- 2.1 Data -- 2.2 Label Generation -- 2.3 CNN Training and Testing -- 2.4 Significance Testing and Gene Set Analysis -- 3 Results -- 3.1 Resnet Comparison -- 3.2 Significant Genes and Pathways -- 3.3 Correlations Between Model Performance and Data Properties -- 3.4 Comparison of Findings with Other Methodologies -- 4 Conclusions -- References -- FAIMI -- De-identification and Obfuscation of Gender Attributes from Retinal Scans -- 1 Introduction -- 1.1 Differential Privacy for Image Obfuscation -- 1.2 Deep Learning for Diabetic Retinopathy and Sex Classification -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Pre-processing -- 2.3 De-identification Framework -- 2.4 Evaluation Framework -- 3 Results -- 3.1 Full Image Snow Results -- 3.2 VS-Snow Results -- 4 Discussion -- 4.1 Privacy-Utility Tradeoff.
4.2 Importance of Vasculature -- 4.3 Limitations and Future Work -- References -- Unveiling Fairness Biases in Deep Learning-Based Brain MRI Reconstruction -- 1 Introduction -- 2 Background -- 2.1 Fairness Definitions -- 2.2 Source of Bias -- 3 Methods -- 4 Experimental Analysis -- 4.1 Dataset and Pre-processing -- 4.2 Implementation Details -- 4.3 Results -- 5 Discussion -- 6 Conclusion -- References -- Brain Matters: Exploring Bias in AI for Neuroimaging Research -- 1 Introduction -- 2 Current Problems -- 2.1 Structural Problems -- 2.2 Specific Biases -- 3 Mitigation Strategies -- 3.1 Collect More Representative Data -- 3.2 Share and Collaborate -- 3.3 Reduce Reliance on Inaccessible Data Collection Methods -- 3.4 Develop Both Generic and Specific Models and Employ Transfer Learning -- 3.5 Consider the Use of Data Augmentation -- 3.6 Raise Awareness of Bias and Engage in PPI -- 4 Limitations -- 5 Conclusion -- References -- Bias in Unsupervised Anomaly Detection in Brain MRI -- 1 Introduction -- 2 Materials and Methods -- 3 Experiments and Results -- 3.1 Baseline Performance -- 3.2 Impact of Bias -- 3.3 Sources of Bias -- 4 Conclusion -- References -- Towards Unraveling Calibration Biases in Medical Image Analysis -- 1 Introduction -- 2 Numerical Experiments on Real Data -- 2.1 Data -- 2.2 Model Training -- 2.3 Platt Scaling -- 2.4 Performance Evaluation -- 2.5 Results -- 3 Synthetic Experiments -- 3.1 Data -- 3.2 Performance Evaluation -- 3.3 Results -- 4 Discussion -- References -- Are Sex-Based Physiological Differences the Cause of Gender Bias for Chest X-Ray Diagnosis? -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Datasets -- 3.2 Sampling Strategy -- 3.3 Experimental Settings -- 4 Results -- 4.1 Model Performance Across Diseases, Gender Ratios, and Datasets -- 4.2 Comparison of Different Sampling Strategies.
4.3 Breast Cropping Does Not Mitigate Gender Biases -- 4.4 Dataset Bias v.s. Model Bias -- 5 Discussion and Conclusions -- References -- Bayesian Uncertainty-Weighted Loss for Improved Generalisability on Polyp Segmentation Task -- 1 Introduction -- 2 Related Work -- 3 Method -- 4 Experiments and Results -- 4.1 Dataset and Experimental Setup -- 4.2 Results -- 5 Conclusion -- References -- Mitigating Bias in MRI-Based Alzheimer's Disease Classifiers Through Pruning of Deep Neural Networks -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data and Preprocess -- 2.2 Debiasing by Pruning -- 3 Experiment -- 3.1 Implementation and Evaluation -- 3.2 Comparison -- 4 Result -- 5 Discussion and Conclusion -- References -- Auditing Unfair Biases in CNN-Based Diagnosis of Alzheimer's Disease -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Description and Preprocessing -- 2.2 Models -- 2.3 Bias Evaluation Metrics -- 3 Results and Discussion -- 3.1 Auditing Fairness with Respect to Model Performance -- 3.2 Auditing Fairness with Respect to Model Calibration -- 4 Conclusions -- References -- Distributionally Robust Optimization and Invariant Representation Learning for Addressing Subgroup Underrepresentation: Mechanisms and Limitations -- 1 Introduction -- 2 Assessing Debiasing Mechanisms -- 2.1 Methodology -- 2.2 Experiments and Results -- 3 Improving the Debiasing of Spurious Correlations -- References -- Analysing Race and Sex Bias in Brain Age Prediction -- 1 Introduction -- 2 Materials and Methods -- 2.1 Bias Analysis -- 3 Results -- 4 Discussion and Conclusion -- A Appendix -- References -- Studying the Effects of Sex-Related Differences on Brain Age Prediction Using Brain MR Imaging -- 1 Introduction -- 2 Materials and Methods -- 2.1 Brain MR Datasets -- 2.2 Pre-processing -- 2.3 Brain Age Prediction Task -- 2.4 Grad-CAM Interpretability.
2.5 Experimental Setting -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- An Investigation into the Impact of Deep Learning Model Choice on Sex and Race Bias in Cardiac MR Segmentation -- 1 Introduction -- 2 Materials -- 3 Methods -- 3.1 Dataset Sampling -- 3.2 Model Architecture and Implementation -- 3.3 Model Evaluation -- 4 Results -- 5 Discussion -- References -- An Investigation into Race Bias in Random Forest Models Based on Breast DCE-MRI Derived Radiomics Features -- 1 Introduction -- 2 Materials -- 3 Methods -- 4 Experiments and Results -- 4.1 Race Classification -- 4.2 Bias Analysis -- 4.3 Covariate Analysis -- 5 Discussion and Conclusions -- References -- How You Split Matters: Data Leakage and Subject Characteristics Studies in Longitudinal Brain MRI Analysis -- 1 Introduction -- 2 Methods -- 2.1 Data Collection and Processing -- 2.2 Training Setup -- 2.3 Evaluation Scheme -- 3 Result -- 4 Discussion and Conclusion -- References -- Revisiting Skin Tone Fairness in Dermatological Lesion Classification -- 1 Introduction -- 2 Methods and Materials -- 2.1 Dataset -- 2.2 Evaluation of Skin Lesion Classification -- 2.3 Skin Tone Estimation -- 3 Experiments and Results -- 3.1 Comparison of ITA Estimation Methods -- 3.2 Fairness Analysis -- 3.3 Simulated Data Shifts -- 4 Conclusions -- References -- A Study of Age and Sex Bias in Multiple Instance Learning Based Classification of Acute Myeloid Leukemia Subtypes -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data -- 2.2 Multiple Instance Learning -- 3 Experiments -- 3.1 Sex Bias -- 3.2 Age Bias -- 4 Results -- 4.1 Sex Bias -- 4.2 Age Bias -- 5 Discussion -- References -- Unsupervised Bias Discovery in Medical Image Segmentation -- 1 Introduction -- 2 Related Work -- 3 Unsupervised Bias Discovery via Reverse Classification Accuracy -- 4 Experiments and Discussion.
4.1 Synthetic Experiment: Validating RCA for UBD.
Record Nr. UNISA-996558469503316
Cham, Switzerland : , : Springer, Springer Nature Switzerland AG, , [2023]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui