Tumor localization in tissue microarrays using rotation invariant superpixel pyramids

Shazia Akbar (Lead / Corresponding author), Lee Jordan, Alastair M. Thompson, Stephen J. McKenna

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

7 Citations (Scopus)
218 Downloads (Pure)

Abstract

Tumor localization is an important component of histopathology image analysis; it has yet to be reliably automated for breast cancer histopathology. This paper investigates the use of superpixel classification to localize tumor regions. A superpixel representation retains information about visual structures such as cellular compartments, connective tissue, lumen and fatty tissue without having to commit to semantic segmentation at this level. In order to localize tumor in large images, a rotation invariant spatial pyramid representation is proposed using bags-of-superpixels. The method is evaluated on expert-annotated oestrogen-receptor stained TMA spots and compared to other superpixel classification techniques. Results demonstrate that it performs favorably.
Original languageEnglish
Title of host publication2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015)
PublisherIEEE
Pages1292-1295
Number of pages4
ISBN (Print)9781467393300
DOIs
Publication statusPublished - 2015
Event2015 IEEE International Symposium on Biomedical Imaging: From Nano to Macro - New York Marriott at Brooklyn Bridge, New York, United States
Duration: 16 Apr 201519 Apr 2015
http://biomedicalimaging.org/2015/

Conference

Conference2015 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Abbreviated titleISBI 2015
Country/TerritoryUnited States
CityNew York
Period16/04/1519/04/15
Internet address

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