AIMC Topic: Pattern Recognition, Automated

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Real-time human pose estimation and gesture recognition from depth images using superpixels and SVM classifier.

Sensors (Basel, Switzerland)
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...

Classification of multiple sclerosis lesions using adaptive dictionary learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This paper presents a sparse representation and an adaptive dictionary learning based method for automated classification of multiple sclerosis (MS) lesions in magnetic resonance (MR) images. Manual delineation of MS lesions is a time-consuming task,...

Annotating risk factors for heart disease in clinical narratives for diabetic patients.

Journal of biomedical informatics
The 2014 i2b2/UTHealth natural language processing shared task featured a track focused on identifying risk factors for heart disease (specifically, Cardiac Artery Disease) in clinical narratives. For this track, we used a "light" annotation paradigm...

Echocardiogram enhancement using supervised manifold denoising.

Medical image analysis
This paper presents data-driven methods for echocardiogram enhancement. Existing denoising algorithms typically rely on a single noise model, and do not generalize to the composite noise sources typically found in real-world echocardiograms. Our meth...

Automated extraction and labelling of the arterial tree from whole-body MRA data.

Medical image analysis
In this work, we present a fully automated algorithm for extraction of the 3D arterial tree and labelling the tree segments from whole-body magnetic resonance angiography (WB-MRA) sequences. The algorithm developed consists of two core parts (i) 3D v...

Efficient multi-atlas abdominal segmentation on clinically acquired CT with SIMPLE context learning.

Medical image analysis
Abdominal segmentation on clinically acquired computed tomography (CT) has been a challenging problem given the inter-subject variance of human abdomens and complex 3-D relationships among organs. Multi-atlas segmentation (MAS) provides a potentially...

Multi-class BCGA-ELM based classifier that identifies biomarkers associated with hallmarks of cancer.

BMC bioinformatics
BACKGROUND: Traditional cancer treatments have centered on cytotoxic drugs and general purpose chemotherapy that may not be tailored to treat specific cancers. Identification of molecular markers that are related to different types of cancers might l...

MR image synthesis by contrast learning on neighborhood ensembles.

Medical image analysis
Automatic processing of magnetic resonance images is a vital part of neuroscience research. Yet even the best and most widely used medical image processing methods will not produce consistent results when their input images are acquired with differen...

Automating the generation of lexical patterns for processing free text in clinical documents.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Many tasks in natural language processing utilize lexical pattern-matching techniques, including information extraction (IE), negation identification, and syntactic parsing. However, it is generally difficult to derive patterns that achiev...

A hybrid method for airway segmentation and automated measurement of bronchial wall thickness on CT.

Medical image analysis
Inflammatory and infectious lung diseases commonly involve bronchial airway structures and morphology, and these abnormalities are often analyzed non-invasively through high resolution computed tomography (CT) scans. Assessing airway wall surfaces an...