AIMC Topic: Magnetic Resonance Imaging

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Diagnostic and Prognostic Classification of Brain Disorders Using Residual Learning on Structural MRI Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this work, we study the potential of the deep residual neural network (ResNet) architecture to learn abstract neuroanatomical alterations in the structural MRI data by evaluating its diagnostic and prognostic classification performance on two larg...

Right Ventricular Segmentation from MRI Using Deep Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The assessment of right ventricular (RV) function is essential in the diagnosis of many cardiac diseases. Magnetic resonance imaging (MRI) offers an excellent solution to image right ventricle non-invasively with high contrast and temporal resolution...

Alzheimer's Disease Brain Network Classification Using Improved Transfer Feature Learning with Joint Distribution Adaptation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Alzheimer's disease significantly affects the quality of life of patients. This paper proposes an approach to identify Alzheimer's disease based on transfer learning using functional MRI images, which is especially useful when the training dataset is...

Prediction of Multiple Sclerosis Patient Disability from Structural Connectivity using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Prediction of disability progression in multiple sclerosis patients is a critical component of their management. In particular, one challenge is to identify and characterize a patient profile who may benefit of efficient treatments. However, it is no...

Body-Mounted MRI-Conditional Parallel Robot for Percutaneous Interventions Structural Improvement, Calibration, and Accuracy Analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
To assist in percutaneous interventions in the lower back under magnetic resonance imaging guidance, a 4 degree-of-freedom body-mounted parallel robot is developed. The robot structure is improved comparatively to a previously developed robot, to inc...

Shoulder-mounted Robot for MRI-Guided Arthrography: Clinically Optimized System.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper introduces our compact and lightweight patient-mounted MRI-compatible 4 degree-of-freedom (DOF) robot with an improved transmission system for MRI-guided arthrography procedures. This robot could make the traditional two-stage arthrography...

[Use AI for Dementia Diagnosis].

Brain and nerve = Shinkei kenkyu no shinpo
Using AI for dementia diagnosis is still in research stage, however some of the work points to the development of new medical devices. One is a voxel-based morphometry analysis of brain atrophy, and a brain network analysis using a resting state func...

Artificial intelligence, osteoporosis and fragility fractures.

Current opinion in rheumatology
PURPOSE OF REVIEW: Artificial intelligence tools have found new applications in medical diagnosis. These tools have the potential to capture underlying trends and patterns, otherwise impossible with previous modeling capabilities. Machine learning an...

An artificial neural network model for clinical score prediction in Alzheimer disease using structural neuroimaging measures.

Journal of psychiatry & neuroscience : JPN
BACKGROUND: The development of diagnostic and prognostic tools for Alzheimer disease is complicated by substantial clinical heterogeneity in prodromal stages. Many neuroimaging studies have focused on case–control classification and predicting conver...