AIMC Topic: Image Interpretation, Computer-Assisted

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Label-aligned multi-task feature learning for multimodal classification of Alzheimer's disease and mild cognitive impairment.

Brain imaging and behavior
Multimodal classification methods using different modalities of imaging and non-imaging data have recently shown great advantages over traditional single-modality-based ones for diagnosis and prognosis of Alzheimer's disease (AD), as well as its prod...

Neural networks improve brain cancer detection with Raman spectroscopy in the presence of operating room light artifacts.

Journal of biomedical optics
Invasive brain cancer cells cannot be visualized during surgery and so they are often not removed. These residual cancer cells give rise to recurrences.

Application of advanced machine learning methods on resting-state fMRI network for identification of mild cognitive impairment and Alzheimer's disease.

Brain imaging and behavior
The study of brain networks by resting-state functional magnetic resonance imaging (rs-fMRI) is a promising method for identifying patients with dementia from healthy controls (HC). Using graph theory, different aspects of the brain network can be ef...

Classification of large-scale fundus image data sets: a cloud-computing framework.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Large medical image data sets with high dimensionality require substantial amount of computation time for data creation and data processing. This paper presents a novel generalized method that finds optimal image-based feature sets that reduce comput...

Automatic detection of neovascularization on optic disk region with feature extraction and support vector machine.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Neovascularization (NV) is a definitive indicator for the onset of Proliferative Diabetic Retinopathy (PDR). The new vessels are fragile and prone to bleed, leading to high risk of sudden vision loss. Automatic detection of NV is an important task in...

Classifying and segmenting microscopy images with deep multiple instance learning.

Bioinformatics (Oxford, England)
MOTIVATION: High-content screening (HCS) technologies have enabled large scale imaging experiments for studying cell biology and for drug screening. These systems produce hundreds of thousands of microscopy images per day and their utility depends on...

A modified fuzzy C-means method for segmenting MR images using non-local information.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: In recent years, MR images have been increasingly used in therapeutic applications such as image-guided radiotherapy (IGRT). However, images with low contrast values and noises present challenges for image segmentation.

Endowing a Content-Based Medical Image Retrieval System with Perceptual Similarity Using Ensemble Strategy.

Journal of digital imaging
Content-based medical image retrieval (CBMIR) is a powerful resource to improve differential computer-aided diagnosis. The major problem with CBMIR applications is the semantic gap, a situation in which the system does not follow the users' sense of ...