Machine Learning in Medical Imaging : 15th International Workshop, MLMI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings, Part I / 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 ; 15241

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 (433 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 2023, 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:

A Novel Momentum-Based Deep Learning Techniques for Medical Image Classification and Segmentation

Generalizable Lymph Node Metastasis Prediction in Pancreatic Cancer

IRUM: An Image Representation and Unified Learning Method for Breast Cancer Diagnosis from Multi-view Ultrasound Images

Classification, Regression and Segmentation directly from k-Space in Cardiac MRI

DDSB: An Unsupervised and Training-free Method for Phase Detection in Echocardiography

Mitral Regurgitation Recogniton based on Unsupervised Out-of-Distribution Detection with Residual Diffusion Amplification

Deep Reinforcement Learning with Multiple Centerline-Guidance for Localization of Left Atrial Appendage Orifice from CT Images

Lung-CADex: Fully automatic Zero-Shot Detection & Classification of Lung Nodules in Thoracic CT Images

CIResDiff: A Clinically-Informed Residual Diffusion Model for Predicting Idiopathic Pulmonary Fibrosis Progression

Vision Transformer Model for Automated End-to-End Radiographic Assessment of Joint Damage in Psoriatic Arthritis

CorticalEvolve: Age-Conditioned Ordinary Differential Equation Model for Cortical Surface Reconstruction

CSR-dMRI: Continuous Super-Resolution of Diffusion MRI with Anatomical Structure-assisted Implicit Neural Representation Learning

Atherosclerotic plaque stability prediction from longitudinal ultrasound images

Leveraging IHC Staining to Prompt HER2 Status Prediction from HE-Stained Histopathology Whole Slide Images

VIMs: Virtual Immunohistochemistry Multiplex staining via Text-to-Stain Diffusion Trained on Uniplex Stains

Structural-Connectivity-guided Functional Connectivity Representation for Multi-modal Brain Disease Classification.-Clinical Brain MRI Super-Resolution with 2D Slice-Wise Diffusion Model

Low-to-high Frequency Progressive K-Space Learning for MRI Reconstruction

LSST: Learned Single-Shot Trajectory and Reconstruction Network for MR Imaging

7T-like T1-weighted and TOF MRI synthesis from 3T MRI with Multi-contrast Complementary Deep Learning

A Probabilistic Hadamard U-Net for MRI Bias Field Correction

Structure-Preserving Diffusion Model for Unpaired Medical Image Translation

Simultaneous Image Quality Improvement and Artefacts Correction in Accelerated MRI

Full-TrSUN: A Full-Resolution Transformer UNet for high quality PET image synthesis

TS-SR3: Time-strided Denoising Diffusion Probabilistic Model for MR Super-resolution

PDM: A Plug-and-Play Perturbed Multi-path Diffusion Module for Simultaneous Medical Image Segmentation Improvement and Uncertainty Estimation

DyNo: Dynamic Normalization based Test-Time Adaptation for 2D Medical Image Segmentation.-Accurate Delineation of Cerebrovascular Structures from TOF-MRA with Connectivity-Reinforced Deep Learning

Learning Instance-Discriminative Pixel Embeddings Using Pixel Triplets

Geo-UNet: A Geometrically Constrained Neural Framework for Clinical-Grade Lumen Segmentation in Intravascular Ultrasound

Domain Influence in MRI Medical Image Segmentation: spatial versus k-space inputs

Enhanced Small Liver Lesion Detection and Segmentation Using a Size-focused Multi-model Approach in CT Scans

Generation and Segmentation of Simulated Total-Body PET Images

Integrating Convolutional Neural Network and Transformer for Lumen Prediction along the Aorta Sections

CSSD: Cross-Supervision and Self-Denoising for Hybrid-Supervised Hepatic Vessel Segmentation

Calibrated Diverse Ensemble Entropy Minimization for Robust Test-Time Adaptation in Prostate Cancer Detection

SpineStyle: Conceptualizing Style Transfer for Image-Guided Spine Surgery on Radiographs

SGSR: Structure-Guided Multi-Contrast MRI Super-Resolution via Spatio-Frequency Co-Query Attention

Knowledge Distillation based Dual-Branch Network for Whole Slide Image Analysis

DHSampling: Diversity-based Hyperedge Sampling in GNN Learning with Application to Medical Imaging Classification.

Notes:

Includes bibliographical references and index.

ISBN:

3-031-73284-7