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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/21479

Title: A perceptual aid to delineating the extent of potential mammographic abnormalities
Authors: Selvan, Arul N.
Chen, Yan
Nevisi, Hossein
Dong, Leng
Wright, Chris
Gale, Alastair G.
Keywords: Radiology
Mammography
Issue Date: 2015
Publisher: BioMed Central (© the authors)
Citation: SELVAN, A. ... et al., 2015. A perceptual aid to delineating the extent of potential mammographic abnormalities [poster]. IN: Proceedings of 2015 British Society of Breast Radiology Annual Scientific Meeting, Nottingham, Great Britain, 9-11 November 2015, poster no. 19.
Abstract: Being able to accurately determine the extent of a possible malignancy on a mammogram is an important task as this can affect the potential follow up surgical treatment that a woman receives after breast screening. It is known that this can be a difficult task, particularly where the lesion has diffuse abnormalities. A potential computer-aided approach is to employ Hierarchical Clustering-based Segmentation (HCS) and this interactive educational exhibit dynamically demonstrates this technique. HCS is an unsupervised segmentation process that when applied to an image yields a hierarchy of segmentations based on image pixel dissimilarities and so can be used to highlight areas in the mammographic image to aid interpretation.
Description: An abstract of this presentation was published as: SELVAN, A. ... et al., 2015. A perceptual aid to delineating the extent of potential mammographic abnormalities. Breast Cancer Research, 17 (Suppl. 1), p.7, DOI: 10.1186/bcr3781.
Version: Accepted for publication
DOI: 10.1186/bcr3781
URI: https://dspace.lboro.ac.uk/2134/21479
Publisher Link: http://dx.doi.org/10.1186/bcr3781
ISSN: 1465-5411
Appears in Collections:Conference Papers and Presentations (Computer Science)

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