FAscicle Lower Leg Muscle Ultrasound Dataset is a dataset composed of 812 ultrasound images of lower leg muscles to analyze muscle weaknesses and prevent injuries.
This dataset is presented in the article AW-Net: Automatic muscle structure analysis on B-mode ultrasound images for injury prevention. It combines the datasets provided by two articles, “Estimating Full Regional Skeletal Muscle Fibre Orientation from B-Mode Ultrasound Images Using Convolutional, Residual, and Deconvolutional Neural Networks” published by Ryan Cunningham et al. and “Automated Analysis of Musculoskeletal Ultrasound Images Using Deep Learning” published by Neil Cronin, with complementary annotations.
The zip file contains the two datasets respectively separated into two folders named by their author. Each image of each dataset has one matching fascicle segmentation mask and one aponeurosis segmentation mask recognizable by name.
