Glaucoma is among the most common causes of permanent blindness in human. Because the initial symptoms are not evident, mass screening would assist early diagnosis in the vast population. Such mass screening requires an automated diagnosis technique....
OBJECTIVE: The purpose of this study is to evaluate the ability of machine learning to discriminate between magnetic resonance images (MRI) of normal and pathological human articular cartilage obtained under standard clinical conditions.
Although decades of efforts have been spent studying the pathogenesis of social anxiety disorder (SAD), there are still no objective biological markers that could be reliably used to identify individuals with SAD. Studies using multivariate pattern a...
Age-related Macular Degeneration (AMD) is an irreversible and chronic medical condition characterized by drusen, Choroidal Neovascularization (CNV) and Geographic Atrophy (GA). AMD is one of the major causes of visual loss among elderly people. It is...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jun 1, 2015
Objective image quality assessment (IQA) plays an important role in the development of multimedia applications. Prediction of IQA metric should be consistent with human perception. The release of the newest IQA database (TID2013) challenges most of t...
In this paper, we present human pose estimation and gesture recognition algorithms that use only depth information. The proposed methods are designed to be operated with only a CPU (central processing unit), so that the algorithm can be operated on a...
Neural networks : the official journal of the International Neural Network Society
May 21, 2015
Standard methods for the analysis of functional MRI data strongly rely on prior implicit and explicit hypotheses made to simplify the analysis. In this work the attention is focused on two such commonly accepted hypotheses: (i) the hemodynamic respon...
BACKGROUND: There are currently no neuroanatomical biomarkers of anorexia nervosa (AN) available to make clinical inferences at an individual subject level. We present results of a multivariate machine learning (ML) approach utilizing structural neur...
Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, ...
BACKGROUND: Profiling gene expression in brain structures at various spatial and temporal scales is essential to understanding how genes regulate the development of brain structures. The Allen Developing Mouse Brain Atlas provides high-resolution 3-D...
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