posted on 2016-06-06, 09:20authored byArul 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.
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.