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Tumor localization in tissue microarrays using rotation invariant superpixel pyramids

Tumor localization in tissue microarrays using rotation invariant superpixel pyramids

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Authors

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

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Info

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
StatePublished - 2015
Event2015 IEEE International Symposium on Biomedical Imaging: From Nano to Macro - New York, United States

Conference

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

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.

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  • Author Accepted Manuscript

    Accepted author manuscript, 929 KB, PDF-document

    © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
    Published in:
    Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on
    16-19 April 2015 Page(s): 1292 - 1295

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