AIMC Topic: Magnetic Resonance Imaging

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Supervised dictionary learning for inferring concurrent brain networks.

IEEE transactions on medical imaging
Task-based fMRI (tfMRI) has been widely used to explore functional brain networks via predefined stimulus paradigm in the fMRI scan. Traditionally, the general linear model (GLM) has been a dominant approach to detect task-evoked networks. However, G...

Predicting long-term outcome of Internet-delivered cognitive behavior therapy for social anxiety disorder using fMRI and support vector machine learning.

Translational psychiatry
Cognitive behavior therapy (CBT) is an effective treatment for social anxiety disorder (SAD), but many patients do not respond sufficiently and a substantial proportion relapse after treatment has ended. Predicting an individual's long-term clinical ...

Geometrical features assessment of liver's tumor with application of artificial neural network evolved by imperialist competitive algorithm.

International journal for numerical methods in biomedical engineering
Geometrical features of a cancerous tumor embedded in biological soft tissue, including tumor size and depth, are a necessity in the follow-up procedure and making suitable therapeutic decisions. In this paper, a new socio-politically motivated globa...

Feature-Preserving Noise Removal.

IEEE transactions on medical imaging
Conventional image restoration algorithms use transform-domain filters, which separate the noise from the sparse signal among the transform components or apply spatial smoothing filters in real space whose design relies on prior assumptions about the...

Comparison of machine classification algorithms for fibromyalgia: neuroimages versus self-report.

The journal of pain
UNLABELLED: Recent studies have posited that machine learning (ML) techniques accurately classify individuals with and without pain solely based on neuroimaging data. These studies claim that self-report is unreliable, making "objective" neuroimaging...

Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.

International journal of geriatric psychiatry
OBJECTIVE: Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and treatment is guided by trial and error instead of evaluating associated underlying brain characteristics. Unlike past studies, we attempted to estimate ...

Multimodal analysis of functional and structural disconnection in Alzheimer's disease using multiple kernel SVM.

Human brain mapping
Alzheimer's disease (AD) patients exhibit alterations in the functional connectivity between spatially segregated brain regions which may be related to both local gray matter (GM) atrophy as well as a decline in the fiber integrity of the underlying ...

Physics instruction induces changes in neural knowledge representation during successive stages of learning.

NeuroImage
Incremental instruction on the workings of a set of mechanical systems induced a progression of changes in the neural representations of the systems. The neural representations of four mechanical systems were assessed before, during, and after three ...

Watershed based intelligent scissors.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Watershed based modification of intelligent scissors has been developed. This approach requires a preprocessing phase with anisotropic diffusion to reduce subtle edges. Then, the watershed transform enhances the corridors. Finally, a roaming procedur...

Discrimination of schizophrenia auditory hallucinators by machine learning of resting-state functional MRI.

International journal of neural systems
Auditory hallucinations (AH) are a symptom that is most often associated with schizophrenia, but patients with other neuropsychiatric conditions, and even a small percentage of healthy individuals, may also experience AH. Elucidating the neural mecha...