AIMC Topic: Magnetic Resonance Imaging

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Development and testing of a deep learning-based strategy for scar segmentation on CMR-LGE images.

Magma (New York, N.Y.)
OBJECTIVE: The aim of this paper is to investigate the use of fully convolutional neural networks (FCNNs) to segment scar tissue in the left ventricle from cardiac magnetic resonance with late gadolinium enhancement (CMR-LGE) images.

Automated detection of imaging features of disproportionately enlarged subarachnoid space hydrocephalus using machine learning methods.

NeuroImage. Clinical
OBJECTIVE: Create an automated classifier for imaging characteristics of disproportionately enlarged subarachnoid space hydrocephalus (DESH), a neuroimaging phenotype of idiopathic normal pressure hydrocephalus (iNPH).

Robotically assisted long bone biopsy under MRI: cadaver study results.

International journal of computer assisted radiology and surgery
RATIONALE AND OBJECTIVES: We have designed and constructed an MR-safe robot made entirely of nonmetallic components with pneumatic actuators and optical encoders. The robot was developed to enable bone biopsies to be performed under magnetic resonanc...

Automated segmentation of knee bone and cartilage combining statistical shape knowledge and convolutional neural networks: Data from the Osteoarthritis Initiative.

Medical image analysis
We present a method for the automated segmentation of knee bones and cartilage from magnetic resonance imagingĀ (MRI) that combines a priori knowledge of anatomical shape with Convolutional Neural Networks (CNNs). The proposed approach incorporates 3D...

Brain dynamics and temporal trajectories during task and naturalistic processing.

NeuroImage
Human functional Magnetic Resonance Imaging (fMRI) data are acquired while participants engage in diverse perceptual, motor, cognitive, and emotional tasks. Although data are acquired temporally, they are most often treated in a quasi-static manner. ...

Machine learning of brain gray matter differentiates sex in a large forensic sample.

Human brain mapping
Differences between males and females have been extensively documented in biological, psychological, and behavioral domains. Among these, sex differences in the rate and typology of antisocial behavior remains one of the most conspicuous and enduring...

Retinal image analytics detects white matter hyperintensities in healthy adults.

Annals of clinical and translational neurology
OBJECTIVE: We investigated whether an automatic retinal image analysis (ARIA) incorporating machine learning approach can identify asymptomatic older adults harboring high burden of white matter hyperintensities (WMH) using MRI as gold standard.

Multi-sequence myocardium segmentation with cross-constrained shape and neural network-based initialization.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
For myocardial infarction (MI) patients, delayed enhancement (DE) and T2-weighted cardiovascular magnetic resonance imaging (CMR) can play significant roles in diagnosis, prognosis and therapeutic strategy evaluation. However, the non-rigid registrat...

Splenomegaly Segmentation on Multi-Modal MRI Using Deep Convolutional Networks.

IEEE transactions on medical imaging
The findings of splenomegaly, abnormal enlargement of the spleen, is a non-invasive clinical biomarker for liver and spleen diseases. Automated segmentation methods are essential to efficiently quantify splenomegaly from clinically acquired abdominal...