Title: A study on indirect immunofluorescence image classification methods for bioinformatics

Authors: B.S. Divya; Kamalraj Subramaniam; H.R. Nanjundaswamy

Addresses: Karpagam Academy of Higher Education, Salem Kochi Highway, Eachanari, Coimbatore, Tamil Nadu 641021, India ' Karpagam Academy of Higher Education, Salem Kochi Highway, Eachanari, Coimbatore, Tamil Nadu 641021, India ' IP Engineering, Microsemi India Private Ltd, Hyderabad, Telangana, 500032, India

Abstract: The indirect immunofluorescence (IIF) test with human epithelial type-2 (HEp-2) cells as substrates is the gold standard for anti-nuclear antibodies (ANA) test to diagnose autoimmune diseases. The specialists in the laboratory visually examine the specimen under microscope to recognise the staining patterns and generate the report. So ANA test is subjective and needs systemic automation for bioinformatics. In this view international benchmarking initiatives were organised by IAPR in the last six years. In this paper the state of the art on IIF HEp-2 cells classification task was analysed. This paper highlighted the original aspects with the detailed discussion of the published methods. Design choice verses performance was analysed.

Keywords: anti-nuclear antibodies; ANA; pattern classification; HEp-2 cell; computer aided diagnosis; CAD; indirect immunofluorescence; IIF; healthcare system.

DOI: 10.1504/IJMEI.2020.111029

International Journal of Medical Engineering and Informatics, 2020 Vol.12 No.6, pp.553 - 567

Received: 20 Nov 2017
Accepted: 18 Jun 2018
Published online: 06 Nov 2020 *

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