AIMC Topic: Image Interpretation, Computer-Assisted

Clear Filters Showing 3011 to 3020 of 3033 articles

Fetal thymus volume estimation by virtual organ computer-aided analysis in normal pregnancies.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: The thymus has a pyramidal shape, which is best shown in coronal planes. The aim of this study was to evaluate the potential of virtual organ computer-aided analysis to estimate fetal thymus volume in normal pregnancies.

Multiple ocular diseases detection based on joint sparse multi-task learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this paper, we present a multiple ocular diseases detection scheme based on joint sparse multi-task learning. Glaucoma, Pathological Myopia (PM), and Age-related Macular Degeneration (AMD) are three major causes of vision impairment and blindness ...

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...

Classification of focal liver lesions on ultrasound images by extracting hybrid textural features and using an artificial neural network.

Bio-medical materials and engineering
This paper focuses on the improvement of the diagnostic accuracy of focal liver lesions by quantifying the key features of cysts, hemangiomas, and malignant lesions on ultrasound images. The focal liver lesions were divided into 29 cysts, 37 hemangio...

Automatic segmentation in image stacks based on multi-constraint level-set evolution.

Bio-medical materials and engineering
Contour extraction of image stacks is a basic task in medical modeling. The existing level-set methods usually suffer from some problems (e.g. serious errors around sharp features, incorrect split of topology and contour occlusions). This paper propo...

Image manifold revealing for breast lesion segmentation in DCE-MRI.

Bio-medical materials and engineering
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is widely used for breast lesion differentiation. Manual segmentation in DCE-MRI is difficult and open to viewer interpretation. In this paper, an automatic segmentation method based on i...

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...