Machine Learning in Medical Imaging : 15th International Workshop, MLMI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings, Part II / edited by Xuanang Xu, Zhiming Cui, Islem Rekik, Xi Ouyang, Kaicong Sun.

Format:

Book

Contributor:

Xu, Xuanang, editor.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 15242

Language:

English

Subjects (All):

Computer vision.

Pattern recognition systems.

Machine learning.

Computer engineering.

Computer networks.

Social sciences--Data processing.

Social sciences.

Bioinformatics.

Computer Vision.

Automated Pattern Recognition.

Machine Learning.

Computer Engineering and Networks.

Computer Application in Social and Behavioral Sciences.

Computational and Systems Biology.

Local Subjects:

Computer Vision.

Automated Pattern Recognition.

Machine Learning.

Computer Engineering and Networks.

Computer Application in Social and Behavioral Sciences.

Computational and Systems Biology.

Physical Description:

1 online resource (263 pages)

Edition:

1st ed. 2025.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2025.

Summary:

This book constitutes the proceedings of the 15th International Workshop on Machine Learning in Medical Imaging, MLMI 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, on October 6, 2024. The 63 full papers presented in this volume were carefully reviewed and selected from 100 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging using artificial intelligence (AI) and machine learning (ML).

Contents:

Robust Box Prompt based SAM for Medical Image Segmentation

Multi-task Learning Approach for Intracranial Hemorrhage Prognosis

Mitigating False Predictions In Unreasonable Body Regions

UniFed: A Universal Federation of a Mixture of Highly Heterogeneous Medical Image Classification Tasks

Tackling domain generalization for out-of-distribution endoscopic imaging

Benchmarking Dependence Measures to Prevent Shortcut Learning in Medical Imaging

Selective Classifier Based Search Space Shrinking for Radiographs Retrieval

Pseudo-Rendering for Resolution and Topology-Invariant Cortical Parcellation

Partially Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation

VIS-MAE: An Efficient Self-Supervised Learning Approach on Medical Image Segmentation and Classification

Transformer-based Parameter Fitting of Models derived from Bloch-McConnell Equations for CEST MRI Analysis

Probabilistic 3D Correspondence Prediction from Sparse Unsegmented Images

StoDIP: Efficient 3D MRF image reconstruction with deep image priors and stochastic iterations

Detection of Emerging Infectious Diseases in Lung CT based on Spatial Anomaly Patterns

Data Alchemy: Mitigating Cross-Site Model Variability Through Test Time Data Calibration

Noise-robust onformal prediction for medical image classification

Identifying Critical Tokens for Accurate Predictions in Transformer-based Medical Imaging Models.-Resource-efficient Medical Image Analysis with Self-adapting Forward-Forward Networks

SDF-Net: A Hybrid Detection Network for Mediastinal Lymph Node Detection on Contrast CT Images

Arges: Spatio-Temporal Transformer for Ulcerative Colitis Severity Assessment in Endoscopy Videos

Characterizing the Histology Spatial Intersections between Tumor-infiltrating Lymphocytes and Tumors for Survival Prediction of Cancers Via Graph Contrastive Learning.-Identifying Nonalcoholic Fatty Liver Disease and Adanced Liver Fibrosis from MRI in UK Biobank

Explainable and Controllable Motion Curve Guided Cardiac Ultrasound Video Generation.

Notes:

Includes bibliographical references and index.

ISBN:

3-031-73290-1