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A convolutional neural network for the automatic diagnosis of collagen VI-related muscular dystrophies

Author
Rodríguez-Bazaga, A.; Roldan, M.; Badosa, M.; Jiménez, C.; Porta, J.
Type of activity
Journal article
Journal
Applied soft computing
Date of publication
2019-12-01
Volume
85
First page
105772:1
Last page
105772:9
DOI
10.1016/j.asoc.2019.105772
Project funding
KINODYN: Kinodynamic planning of efficient and agile robot motions
Repository
http://hdl.handle.net/2117/175193 Open in new window
URL
https://www.sciencedirect.com/science/article/abs/pii/S1568494619305538 Open in new window
Abstract
The development of machine learning systems for the diagnosis of rare diseases is challenging, mainly due to the lack of data to study them. This paper surmounts this obstacle and presents the first Computer-Aided Diagnosis (CAD) system for low-prevalence collagen VI-related congenital muscular dystrophies. The proposed CAD system works on images of fibroblast cultures obtained with a confocal microscope and relies on a Convolutional Neural Network (CNN) to classify patches of such images in two...
Citation
Rodríguez-Bazaga, A. [et al.]. A Convolutional Neural Network for the automatic diagnosis of collagen VI-related muscular dystrophies. "Applied soft computing", 1 Desembre 2019, vol. 85, p. 105772:1-105772:9.
Keywords
Classification, Computer aided diagnosis, Confocal microscopy images, Convolutional neural networks, Deep learning
Group of research
KRD - Kinematics and Robot Design

Participants