AIMC Topic: Neuromuscular Diseases
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Deep learning-based acceleration of muscle water T2 mapping in patients with neuromuscular diseases by more than 50% - translating quantitative MRI from research to clinical routine.
PloS one
Apr 16, 2025
BACKGROUND: Quantitative muscle water T2 (T2w) mapping is regarded as a biomarker for disease activity and response to treatment in neuromuscular diseases (NMD). However, the implementation in clinical settings is limited due to long scanning times a...
A first explainable-AI-based workflow integrating forward-forward and backpropagation-trained networks of label-free multiphoton microscopy images to assess human biopsies of rare neuromuscular disease.
Computer methods and programs in biomedicine
Mar 21, 2025
BACKGROUND AND OBJECTIVE: Diagnosis of rare neuromuscular diseases often relies on muscle biopsy analysis, which varies based on the evaluator's experience. Advances in deep learning show promise in improving diagnostic accuracy by identifying standa...
Importance of neural network complexity for the automatic segmentation of individual thigh muscles in MRI images from patients with neuromuscular diseases.
Magma (New York, N.Y.)
Jan 11, 2025
OBJECTIVE: Segmentation of individual thigh muscles in MRI images is essential for monitoring neuromuscular diseases and quantifying relevant biomarkers such as fat fraction (FF). Deep learning approaches such as U-Net have demonstrated effectiveness...
Humans
Male
Female
Thigh
Aged
Muscle, Skeletal
Image Processing, Computer-Assisted
Middle Aged
Neural Networks, Computer
Reproducibility of Results
Image Interpretation, Computer-Assisted
Adult
Algorithms
Adipose Tissue
Magnetic Resonance Imaging
Neuromuscular Diseases
Deep Learning
Databases, Factual
Myo-regressor Deep Informed Neural NetwOrk (Myo-DINO) for fast MR parameters mapping in neuromuscular disorders.
Computer methods and programs in biomedicine
Aug 28, 2024
Magnetic Resonance (MR) parameters mapping in muscle Magnetic Resonance Imaging (mMRI) is predominantly performed using pattern recognition-based algorithms, which are characterised by high computational costs and scalability issues in the context of...
Towards a diagnostic tool for neurological gait disorders in childhood combining 3D gait kinematics and deep learning.
Computers in biology and medicine
Feb 3, 2024
Gait abnormalities are frequent in children and can be caused by different pathologies, such as cerebral palsy, neuromuscular disease, toe walker syndrome, etc. Analysis of the "gait pattern" (i.e., the way the person walks) using 3D analysis provide...
Combining FES and Exoskeletons in a Hybrid Haptic System for Enhancing VR Experience.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Dec 8, 2023
Robotic technology and functional electrical stimulation (FES) have emerged as highly effective rehabilitative techniques for individuals with neuromuscular diseases, showcasting their ability to restore motor functions. Within the proposed study, we...
The Impact of Fatty Infiltration on MRI Segmentation of Lower Limb Muscles in Neuromuscular Diseases: A Comparative Study of Deep Learning Approaches.
Journal of magnetic resonance imaging : JMRI
Apr 6, 2023
BACKGROUND: Deep learning methods have been shown to be useful for segmentation of lower limb muscle MRIs of healthy subjects but, have not been sufficiently evaluated on neuromuscular disease (NDM) patients.
Editorial for "The Impact of Fatty Infiltration on MRI Segmentation of Lower Limb Muscles in Neuromuscular Diseases: A Comparative Study of Deep Learning Approaches".
Journal of magnetic resonance imaging : JMRI
Apr 6, 2023
Deep learning segmentation of transverse musculoskeletal ultrasound images for neuromuscular disease assessment.
Computers in biology and medicine
Jul 1, 2021
Ultrasound imaging is a patient-friendly and robust technique for studying physiological and pathological muscles. An automatic deep learning (DL) system for the analysis of ultrasound images could be useful to support an expert operator, allowing th...
Effects of gait training with a voluntary-driven wearable cyborg, Hybrid Assistive Limb (HAL), on quality of life in patients with neuromuscular disease, able to walk independently with aids.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
May 15, 2021
Robot-assisted gait training using a voluntary-driven wearable cyborg, Hybrid Assistive Limb (HAL), has been shown to improve the mobility of patients with neurological disorders; however, its effect on the quality of life (QOL) of patients is not cl...
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