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A perceptual aid to delineating the extent of potential mammographic abnormalities

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posted on 06.06.2016 by Arul N. Selvan, Yan Chen, Hossein Nevisi, Leng Dong, Chris Wright, Alastair Gale
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.

History

School

  • Science

Department

  • Computer Science

Published in

Breast Cancer Research

Volume

17

Issue

Suppl 1

Pages

p19 - p19

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.

Publisher

BioMed Central (© the authors)

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

Publication date

2015

Notes

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.

ISSN

1465-5411

eISSN

1465-542X

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Exports