Multifractal Analysis of Histopathological Tissue Images (2011)
Type of ContentConference Contributions - Published
PublisherUniversity of Canterbury. Computer Science and Software Engineering
University of Canterbury. Human Interface Technology Laboratory
Histopathological classification and grading of biopsy specimens play an important role in early cancer detection and prognosis. Nottingham scoring system is one of the standard grading procedures used in breast cancer assessment, where three parameters, Mitotic Count (MC), Nuclear Pleomorphism (NP), and Tubule Formation (TF) are used for prognostic information. The grading takes into account the deviations in cellular structures and appearance from normal, using measures such as density, size, colour and regularity. Cell structures in tissue images are also known to exhibit multifractal characteristics. This paper looks at the multifractal properties of several graded biopsy specimens and analyses the dependency and variation of the fractal parameters with respect to the scores assigned by pathologists.
CitationTay, C., Mukundan, R., Racoceanu, D. (2011) Multifractal Analysis of Histopathological Tissue Images. Auckland, New Zealand: 26th International Conference Image and Vision Computing New Zealand (IVCNZ 2011), 29 Nov-1 Dec 2011. 80-85.
This citation is automatically generated and may be unreliable. Use as a guide only.
Keywordsbreast cancer assessment; multifractal spectra; image analysis; histopathological classification; feature detection; cancer grading
ANZSRC Fields of Research11 - Medical and Health Sciences::1112 - Oncology and Carcinogenesis::111201 - Cancer Cell Biology
46 - Information and computing sciences::4603 - Computer vision and multimedia computation::460306 - Image processing
Rights"©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Showing items related by title, author, creator and subject.
A Robust Algorithm for Automated HER2 Scoring in Breast Cancer Histology Slides Using Characteristic Curves Mukundan R (Springer Verlag (Germany), 2017)This paper presents a novel feature descriptor and classification algorithms for automated scoring of HER2 in Whole Slide Images (WSI). Since a large amount of processing is involved in analyzing WSI images, the ...
Her2 Challenge Contest: A Detailed Assessment of Automated Her2 Scoring Algorithms in Whole Slide Images of Breast Cancer Tissues Qaiser T; Mukherjee A; Pb CR; Munugoti SD; Tallam V; Pitkäaho T; Lehtimäki T; Naughton T; Berseth M; Pedraza A; Mukundan R; Smith M; Bhalerao A; Rodner E; Simon M; Denzler J; Huang C-H; Bueno G; Snead D; Ellis I; Ilyas M; Rajpoot N (2018)Evaluating expression of the Human epidermal growth factor receptor 2 (Her2) by visual examination of immunohistochemistry (IHC) on invasive breast cancer (BCa) is a key part of the diagnostic assessment of BCa due to ...
Ibrahim, M.A.; Mukundan, R. (University of Canterbury. Computer Science and Software Engineering, 2015)The previous studies demonstrated the effectiveness of the multi-fractal based method for the classification of histo-pathological cases by calculating the local singularity coefficients of an image using different intensity ...