AIMC Topic: Paraspinal Muscles

Clear Filters Showing 1 to 10 of 13 articles

Muscle-Driven prognostication in gastric cancer: A multicenter deep learning framework integrating Iliopsoas and erector spinae radiomics for 5-Year survival prediction.

Scientific reports
This study developed a 5-year survival prediction model for gastric cancer patients by combining radiomics and deep learning, focusing on CT-based 2D and 3D features of the iliopsoas and erector spinae muscles. Retrospective data from 705 patients ac...

Prediction of lumbar disc degeneration based on interpretable machine learning models: retrospective cohort study.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: The paraspinal muscles play a critical role in maintaining lumbar spine stability, and different muscles may have varying impacts on lumbar disc degeneration (LDD). However, studies exploring these relationships remain relatively ...

Cooking loss estimation of semispinalis capitis muscle of pork butt using a deep neural network on hyperspectral data.

Meat science
This study evaluated the performance of a deep-learning-based model that predicted cooking loss in the semispinalis capitis (SC) muscle of pork butts using hyperspectral images captured 24 h postmortem. To overcome low-scale samples, 70 pork butts we...

Enhancing ergonomics in E-waste disassembly: the impact of collaborative robotics on muscle activation and coordination.

Ergonomics
Disassembly, as a part of the electronic waste (e-waste) management process, is a labour-intensive task. The emergence of collaborative robots (cobots) provides a robotic solution to reduce the human efforts during disassembly. This study evaluated m...

An Efficient Muscle Segmentation Method via Bayesian Fusion of Probabilistic Shape Modeling and Deep Edge Detection.

IEEE transactions on bio-medical engineering
OBJECTIVE: Paraspinal muscle segmentation and reconstruction from MR images are critical to implement quantitative assessment of chronic and recurrent low back pains. Due to unclear muscle boundaries and shape variations, current segmentation methods...

Cross-sectional area and fat infiltration of the lumbar spine muscles in patients with back disorders: a deep learning-based big data analysis.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: Validated deep learning models represent a valuable option to perform large-scale research studies aiming to evaluate muscle quality and quantity of paravertebral lumbar muscles at the population level. This study aimed to assess lumbar spin...

An externally validated deep learning model for the accurate segmentation of the lumbar paravertebral muscles.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: Imaging studies about the relevance of muscles in spinal disorders, and sarcopenia in general, require the segmentation of the muscles in the images which is very labour-intensive if performed manually and poses a practical limit to the numb...

Deep learning for automatic segmentation of paraspinal muscle on computed tomography.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Muscle quantification is an essential step in sarcopenia evaluation.

Muscle network topology analysis for the classification of chronic neck pain based on EMG biomarkers extracted during walking.

PloS one
Neuromuscular impairments are frequently observed in patients with chronic neck pain (CNP). This study uniquely investigates whether changes in neck muscle synergies detected during gait are sensitive enough to differentiate between people with and w...