AIMC Topic: Magnetic Resonance Imaging

Clear Filters Showing 5491 to 5500 of 6780 articles

DeepNAT: Deep convolutional neural network for segmenting neuroanatomy.

NeuroImage
We introduce DeepNAT, a 3D Deep convolutional neural network for the automatic segmentation of NeuroAnaTomy in T1-weighted magnetic resonance images. DeepNAT is an end-to-end learning-based approach to brain segmentation that jointly learns an abstra...

MRI guided focused ultrasound robotic system for animal experiments.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: In this paper an MRI-guided focused ultrasound (MRgFUS) robotic system was developed that can be used for conducting experiments in small animals.The target for this robotic system regarding motion was to move a therapeutic ultrasound tra...

An interactive medical image segmentation framework using iterative refinement.

Computers in biology and medicine
Segmentation is often performed on medical images for identifying diseases in clinical evaluation. Hence it has become one of the major research areas. Conventional image segmentation techniques are unable to provide satisfactory segmentation results...

Separating generalized anxiety disorder from major depression using clinical, hormonal, and structural MRI data: A multimodal machine learning study.

Brain and behavior
BACKGROUND: Generalized anxiety disorder (GAD) is difficult to recognize and hard to separate from major depression (MD) in clinical settings. Biomarkers might support diagnostic decisions. This study used machine learning on multimodal biobehavioral...

Association between abnormal brain functional connectivity in children and psychopathology: A study based on graph theory and machine learning.

The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry
OBJECTIVES: One of the major challenges facing psychiatry is how to incorporate biological measures in the classification of mental health disorders. Many of these disorders affect brain development and its connectivity. In this study, we propose a n...

Autodelineation of cervical cancers using multiparametric magnetic resonance imaging and machine learning.

Acta oncologica (Stockholm, Sweden)
BACKGROUND: Tumour delineation is a challenging, time-consuming and complex part of radiotherapy planning. In this study, an automatic method for delineating locally advanced cervical cancers was developed using a machine learning approach.

Sensory tractography and robot-quantified proprioception in hemiparetic children with perinatal stroke.

Human brain mapping
Perinatal stroke causes most hemiparetic cerebral palsy, resulting in lifelong disability. We have demonstrated the ability of robots to quantify sensory dysfunction in hemiparetic children but the relationship between such deficits and sensory tract...

A magnetic resonance image-guided breast needle intervention robot system: overview and design considerations.

International journal of computer assisted radiology and surgery
PURPOSE: We developed an image-guided intervention robot system that can be operated in a magnetic resonance (MR) imaging gantry. The system incorporates a bendable needle intervention robot for breast cancer patients that overcomes the space limitat...

ISSLS PRIZE IN BIOENGINEERING SCIENCE 2017: Automation of reading of radiological features from magnetic resonance images (MRIs) of the lumbar spine without human intervention is comparable with an expert radiologist.

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
STUDY DESIGN: Investigation of the automation of radiological features from magnetic resonance images (MRIs) of the lumbar spine.