Applications of Medical Artificial Intelligence

Name: Applications of Medical Artificial Intelligence | First International Workshop, AMAI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings
Brand: Springer
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First International Workshop, AMAI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings

Shandong Wu Behrouz Shabestari Lei Xing(Editor)

Springer (Publisher)

Published on 30. September 2022

VIII, 162 pages

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978-3-031-17721-7 (ISBN)

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Content

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
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Applications of Medical Artificial Intelligence

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