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• W1964710322 abstract "This paper presents image and video analysis based schemes to automate the process of adductors angle measurement which is carried out on infants as a part of Hammersmith Infant Neurological Examination (HINE). Image segmentation, thinning and feature point based object tracking are used for automating the analysis. Segmentation outputs are processed with a novel region merging algorithm. It is found that the refined segmentation outputs can successfully be used to extract features in the context of the application under consideration. Next, a heuristic based filtering algorithm is applied on the thinned structures for locating necessary points to measure adductors angle. A semi-automatic scheme based on the object tracking of a video has been proposed to minimize errors of the image based analysis. It is observed that the video-based analysis outperforms the image-based method. A fully automatic method has also been proposed and compared with the semi-automatic algorithm. The proposed methods have been tested with several videos recorded from hospitals and the results have been found to be satisfactory in the present context." @default.
• W1964710322 created "2016-06-24" @default.
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• W1964710322 date "2012-09-01" @default.
• W1964710322 modified "2023-10-13" @default.
• W1964710322 title "Analysis of adductors angle measurement in Hammersmith infant neurological examinations using mean shift segmentation and feature point based object tracking" @default.
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• W1964710322 doi "https://doi.org/10.1016/j.compbiomed.2012.07.005" @default.
• W1964710322 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/22841364" @default.
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