Back to Search
Start Over
Deep Learning of Ultrasound Imaging for Evaluating Ambulatory Function of Individuals with Duchenne Muscular Dystrophy
- Source :
- Diagnostics, Volume 11, Issue 6, Diagnostics, Vol 11, Iss 963, p 963 (2021)
- Publication Year :
- 2021
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2021.
-
Abstract
- Duchenne muscular dystrophy (DMD) results in loss of ambulation and premature death. Ultrasound provides real-time, safe, and cost-effective routine examinations. Deep learning allows the automatic generation of useful features for classification. This study utilized deep learning of ultrasound imaging for classifying patients with DMD based on their ambulatory function. A total of 85 individuals (including ambulatory and nonambulatory subjects) underwent ultrasound examinations of the gastrocnemius for deep learning of image data using LeNet, AlexNet, VGG-16, VGG-16TL, VGG-19, and VGG-19TL models (the notation TL indicates fine-tuning pretrained models). Gradient-weighted class activation mapping (Grad-CAM) was used to visualize features recognized by the models. The classification performance was evaluated using the confusion matrix and receiver operating characteristic (ROC) curve analysis. The results show that each deep learning model endows muscle ultrasound imaging with the ability to enable DMD evaluations. The Grad-CAMs indicated that boundary visibility, muscular texture clarity, and posterior shadowing are relevant sonographic features recognized by the models for evaluating ambulatory function. Of the proposed models, VGG-19 provided satisfying classification performance (the area under the ROC curve: 0.98<br />accuracy: 94.18%) and feature recognition in terms of physical characteristics. Deep learning of muscle ultrasound is a potential strategy for DMD characterization.
- Subjects :
- Duchenne muscular dystrophy
Medicine (General)
medicine.medical_specialty
Clinical Biochemistry
Article
03 medical and health sciences
ultrasound imaging
R5-920
0302 clinical medicine
Physical medicine and rehabilitation
medicine
030304 developmental biology
0303 health sciences
Receiver operating characteristic
business.industry
Deep learning
Ultrasound
Feature recognition
Confusion matrix
deep learning
medicine.disease
Ambulatory
Ultrasound imaging
Artificial intelligence
business
030217 neurology & neurosurgery
Subjects
Details
- Language :
- English
- ISSN :
- 20754418
- Database :
- OpenAIRE
- Journal :
- Diagnostics
- Accession number :
- edsair.doi.dedup.....1f1b2cdc0b8f7f88fae7cfb3de1996b0
- Full Text :
- https://doi.org/10.3390/diagnostics11060963