Machine learning-driven Heckmatt grading in facioscapulohumeral muscular dystrophy: A novel pathway for musculoskeletal ultrasound analysis

Published: 11 February 2025| Version 1 | DOI: 10.17632/yzg86vb895.1
Contributors:
Francesco Marzola,
,
,

Description

The “Machine Learning-Driven Heckmatt Grading in Facioscapulohumeral Muscular Dystrophy” dataset provides a comprehensive collection of musculoskeletal ultrasound images, associated segmentation masks, model configurations, and relevant subject information aimed at facilitating advanced research in neuromuscular disease diagnostics. Built around the Heckmatt grading system, this dataset supports precise muscle characterization and classification, enabling clinicians and researchers to efficiently explore the diagnostic potential of automated ultrasound image analysis. By leveraging both binary and multi-label segmentation strategies, it offers a flexible framework to study muscle texture across various muscle groups and anatomical sites.

Files

Steps to reproduce

Please follow instructions at: https://github.com/frmrz/Machine-learning-driven-Heckmatt-grading-in-facioscapulohumeral-muscular-dystrophy

Institutions

Radboudumc, Politecnico di Torino

Categories

Ultrasonics, Image Segmentation, Muscle Disorder, Image Classification, Muscular Dystrophy, Medical Ultrasound, Image Analysis

Licence