Discovery - University of Dundee - Online Publications

Library & Learning Centre

First step for computer assisted evaluation of qualatitive supersonic shear wave elastography characteristics in breast tissue.

First step for computer assisted evaluation of qualatitive supersonic shear wave elastography characteristics in breast tissue.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

View graph of relations

Authors

Research units

Info

Original languageEnglish
Title of host publication2016 IEEE 13th International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI 2016 - Proceedings
PublisherIEEE
Pages481-484
Number of pages4
Volume2016-June
ISBN (Electronic)9781479923496
ISBN (Print)9781479923502
DOIs
StatePublished - 16 Jun 2016
Event2016 IEEE 13th International Symposium on Biomedical Imaging - Prague, Czech Republic

Conference

Conference2016 IEEE 13th International Symposium on Biomedical Imaging
Abbreviated titleISBI 2016
CountryCzech Republic
CityPrague
Period13/04/1616/04/16
Internet address

Abstract

The addition of shear wave elastography (SWE) imaging to standard B-mode ultrasound assessment supports the differ-ential diagnosis of solid breast lesions. One way to assess SWE images is qualitative evaluation of the stiffness pattern according to the Tozaki classification. Until now this qualitative assessment has only been possible manually and so has low reproducibility and high inter-observer variability. Thus, this work aims to investigate the feasibility of automatic assessment of Tozaki categories. SWE images of 41 solid breast lesions (9 benign, 32 malignant) were assessed manually by a radiologist and automatically. The results were compared to the histology of the lesions. The diagnostic performance of the automatic assessment is similar to the manual assessment. The algorithm introduced in this work demonstrates the ability to automatically assess qualitative SWE features, given segmented lesions, according to the Tozaki classification.

Download statistics

No data available

Documents

Open Access permissions

Open

Documents

DOI

Library & Learning Centre

Contact | Accessibility | Policy