AIMC Topic: Image Processing, Computer-Assisted

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Robust supervised segmentation of neuropathology whole-slide microscopy images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Alzheimer's disease is characterized by brain pathological aggregates such as Aβ plaques and neurofibrillary tangles which trigger neuroinflammation and participate to neuronal loss. Quantification of these pathological markers on histological sectio...

Segmentation of acne lesion using fuzzy C-means technique with intelligent selection of the desired cluster.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Segmentation is the basic and important step for digital image analysis and understanding. Segmentation of acne lesions in the visual spectrum of light is very challenging due to factors such as varying skin tones due to ethnicity, camera calibration...

A unified framework for automatic wound segmentation and analysis with deep convolutional neural networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Wound surface area changes over multiple weeks are highly predictive of the wound healing process. Furthermore, the quality and quantity of the tissue in the wound bed also offer important prognostic information. Unfortunately, accurate measurements ...

Unsupervised detection of liver lesions in CT images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This work presents an automatic approach for liver lesions detection in CT images. In this approach, liver is first segmented using fast and reliable semi-automatic technique. After liver segmentation, lesion detection is formulated as an unsupervise...

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...

A Hybrid Loss for Multiclass and Structured Prediction.

IEEE transactions on pattern analysis and machine intelligence
We propose a novel hybrid loss for multiclass and structured prediction problems that is a convex combination of a log loss for Conditional Random Fields (CRFs) and a multiclass hinge loss for Support Vector Machines (SVMs). We provide a sufficient c...

Architecture and biological applications of artificial neural networks: a tuberculosis perspective.

Methods in molecular biology (Clifton, N.J.)
Advancement of science and technology has prompted researchers to develop new intelligent systems that can solve a variety of problems such as pattern recognition, prediction, and optimization. The ability of the human brain to learn in a fashion tha...

Clinical prediction from structural brain MRI scans: a large-scale empirical study.

Neuroinformatics
Multivariate pattern analysis (MVPA) methods have become an important tool in neuroimaging, revealing complex associations and yielding powerful prediction models. Despite methodological developments and novel application domains, there has been litt...