A Research on Automation Diagonsis of Pattern Recognition in Stained HEP-2 Cells
C C Manju1, M. Victor Jose2
1C C Manju, Research Scholar, Department of Computer Science and Engineering, Noorul Islam Center for Higher Education, Kumaracoil (Tamil Nadu), India.
2Dr. M. Victor Jose, Associate Professor, Department of Computer Science and Engineering, Noorul Islam Center for Higher Education, Kumaracoil (Tamil Nadu), India.
Manuscript received on 06 September 2019 | Revised Manuscript received on 15 September 2019 | Manuscript Published on 26 October 2019 | PP: 337-345 | Volume-8 Issue-11S2 September 2019 | Retrieval Number: K105509811S219/2019©BEIESP | DOI: 10.35940/ijitee.K1055.09811S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Diagnosis of autoimmune diseases can be achieved via Indirect Immunofluorescence (IIF) images using human epithelial (HEp-2) cell as substrate in laboratory. The automation of this diagnosis method is still challenging because of using various liquids to fix the HEp-2 cells in the slides. Due to various fixation methods, nuclear morphology of cell suffers high variability. This survey reviews all the difficulties in the analysis and recognition of pattern recognition and surveys various image processing techniques which leads to the automation diagnosis. This work consist of advantages and disadvantages of various procedures. Eventually, comparison of their corresponding results are presented. I assure that this initial work may attract many medical image processing researchers to enter into this field.
Keywords: Autoimmune Diagnostic; Antinuclear Antibodies; Pattern Recognition; HEp-2 Cells.
Scope of the Article: Pattern Recognition