AIMC Topic: Brain

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Semi-supervised manifold learning with affinity regularization for Alzheimer's disease identification using positron emission tomography imaging.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Dementia, Alzheimer's disease (AD) in particular is a global problem and big threat to the aging population. An image based computer-aided dementia diagnosis method is needed to providing doctors help during medical image examination. Many machine le...

Brain tissue segmentation using fuzzy clustering techniques.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Medical image segmentation is an essential step for most consequent image analysis tasks. Medical images can be segmented manually, but the accuracy of image segmentation using the automated segmentation algorithms is more when compared w...

A robo-pigeon based on an innovative multi-mode telestimulation system.

Bio-medical materials and engineering
In this paper, we describe a new multi-mode telestimulation system for brain-microstimulation for the navigation of a robo-pigeon, a new type of bio-robot based on Brain-Computer Interface (BCI) techniques. The multi-mode telestimulation system overc...

Automatic brain MR image denoising based on texture feature-based artificial neural networks.

Bio-medical materials and engineering
Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, no...

Identification of Conversion from Normal Elderly Cognition to Alzheimer's Disease using Multimodal Support Vector Machine.

Journal of Alzheimer's disease : JAD
Alzheimer's disease (AD) is one of the most serious progressive neurodegenerative diseases among the elderly, therefore the identification of conversion to AD at the earlier stage has become a crucial issue. In this study, we applied multimodal suppo...

Applying Automated MR-Based Diagnostic Methods to the Memory Clinic: A Prospective Study.

Journal of Alzheimer's disease : JAD
Several studies have demonstrated that fully automated pattern recognition methods applied to structural magnetic resonance imaging (MRI) aid in the diagnosis of dementia, but these conclusions are based on highly preselected samples that significant...

Segmenting the Brain Surface from CT Images with Artifacts Using Dictionary Learning for Non-rigid MR-CT Registration.

Information processing in medical imaging : proceedings of the ... conference
This paper presents a dictionary learning-based method to segment the brain surface in post-surgical CT images of epilepsy patients following surgical implantation of electrodes. Using the electrodes identified in the post-implantation CT, surgeons r...

Prediction of Longitudinal Development of Infant Cortical Surface Shape Using a 4D Current-Based Learning Framework.

Information processing in medical imaging : proceedings of the ... conference
Understanding the early dynamics of the highly folded human cerebral cortex is still an actively evolving research field teeming with unanswered questions. Longitudinal neuroimaging analysis and modeling have become the new trend to advance research ...

Shape Classification Using Wasserstein Distance for Brain Morphometry Analysis.

Information processing in medical imaging : proceedings of the ... conference
Brain morphometry study plays a fundamental role in medical imaging analysis and diagnosis. This work proposes a novel framework for brain cortical surface classification using Wasserstein distance, based on uniformization theory and Riemannian optim...