AIMC Topic: Magnetic Resonance Imaging

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Multivariate decoding of cerebral blood flow measures in a clinical model of on-going postsurgical pain.

Human brain mapping
Recent reports of multivariate machine learning (ML) techniques have highlighted their potential use to detect prognostic and diagnostic markers of pain. However, applications to date have focussed on acute experimental nociceptive stimuli rather tha...

Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects.

NeuroImage
Mild cognitive impairment (MCI) is a transitional stage between age-related cognitive decline and Alzheimer's disease (AD). For the effective treatment of AD, it would be important to identify MCI patients at high risk for conversion to AD. In this s...

Manifold regularized multitask feature learning for multimodality disease classification.

Human brain mapping
Multimodality based methods have shown great advantages in classification of Alzheimer's disease (AD) and its prodromal stage, that is, mild cognitive impairment (MCI). Recently, multitask feature selection methods are typically used for joint select...

Resting state fMRI feature-based cerebral glioma grading by support vector machine.

International journal of computer assisted radiology and surgery
PURPOSEĀ : Tumor grading plays an essential role in the optimal selection of solid tumor treatment. Noninvasive methods are needed for clinical grading of tumors. This study aimed to extract parameters of resting state blood oxygenation level-dependen...

Anatomical dimensions using preoperative magnetic resonance imaging: impact on the learning curve of robot-assisted laparoscopic prostatectomy.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVE: To evaluate the impact of anatomical dimensions as measured using preoperative magnetic resonance imaging on the outcomes of robot-assisted laparoscopic prostatectomy.

Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model.

European child & adolescent psychiatry
Identifying early-onset schizophrenia spectrum disorders (SSD) at a very early stage remains challenging. To assess the diagnostic predictive value of multiple types of data at the emergence of early-onset first-episode psychosis (FEP), various suppo...

Diagnostic classification of specific phobia subtypes using structural MRI data: a machine-learning approach.

Journal of neural transmission (Vienna, Austria : 1996)
While neuroimaging research has advanced our knowledge about fear circuitry dysfunctions in anxiety disorders, findings based on diagnostic groups do not translate into diagnostic value for the individual patient. Machine-learning generates predictiv...

A data-driven approach to prostate cancer detection from dynamic contrast enhanced MRI.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Magnetic resonance imaging (MRI), particularly dynamic contrast enhanced (DCE) imaging, has shown great potential in prostate cancer diagnosis and staging. In the current practice of DCE-MRI, diagnosis is based on quantitative parameters extracted fr...