AI Medical Compendium Topic

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Spinal Cord

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[Effects of mild moxibustion on Beclin-1/Bcl-2 expression in spinal cord of rats with cervical spondylotic radiculopathy].

Zhen ci yan jiu = Acupuncture research
OBJECTIVE: To observe the effects of mild moxibustion on the expression of autophagy and apoptosis factors Beclin-1, Bcl-2 mRNA and protein in spinal cord (including nerve root tissues) of cervical spondylotic radiculopathy (CSR) rats, so as to explo...

Open-source pipeline for multi-class segmentation of the spinal cord with deep learning.

Magnetic resonance imaging
This paper presents an open-source pipeline to train neural networks to segment structures of interest from MRI data. The pipeline is tailored towards homogeneous datasets and requires relatively low amounts of manual segmentations (few dozen, or les...

A supervised machine learning approach to characterize spinal network function.

Journal of neurophysiology
Spontaneous activity is a common feature of immature neuronal networks throughout the central nervous system and plays an important role in network development and consolidation. In postnatal rodents, spontaneous activity in the spinal cord exhibits ...

Robot controlled, continuous passive movement of the ankle reduces spinal cord excitability in participants with spasticity: a pilot study.

Experimental brain research
Spasticity of the ankle reduces quality of life by impeding walking and other activities of daily living. Robot-driven continuous passive movement (CPM) is a strategy for lower limb spasticity management but effects on spasticity, walking ability and...

Neural Interactions in Developing Rhythmogenic Spinal Networks: Insights From Computational Modeling.

Frontiers in neural circuits
The mechanisms involved in generation of rhythmic locomotor activity in the mammalian spinal cord remain poorly understood. These mechanisms supposedly rely on both intrinsic properties of constituting neurons and interactions between them. A subset ...

Automatic segmentation of pelvic organs-at-risk using a fusion network model based on limited training samples.

Acta oncologica (Stockholm, Sweden)
Efficient and accurate methods are needed to automatically segmenting organs-at-risk (OAR) to accelerate the radiotherapy workflow and decrease the treatment wait time. We developed and evaluated the use of a fused model Dense V-Network for its abil...

Comparison between atlas and convolutional neural network based automatic segmentation of multiple organs at risk in non-small cell lung cancer.

Medicine
Delineation of organs at risk (OARs) is important but time consuming for radiotherapy planning. Automatic segmentation of OARs based on convolutional neural network (CNN) has been established for lung cancer patients at our institution. The aim of th...

The CPGs for Limbed Locomotion-Facts and Fiction.

International journal of molecular sciences
The neuronal networks that generate locomotion are well understood in swimming animals such as the lamprey, zebrafish and tadpole. The networks controlling locomotion in tetrapods remain, however, still enigmatic with an intricate motor pattern requi...

Combining Reflexes and External Sensory Information in a Neuromusculoskeletal Model to Control a Quadruped Robot.

IEEE transactions on cybernetics
This article examines the importance of integrating locomotion and cognitive information for achieving dynamic locomotion from a viewpoint combining biology and ecological psychology. We present a mammalian neuromusculoskeletal model from external se...