Automatic reconstruction of overlapped cells in breast cancer FISH images. (15th December 2019)

• Record Type: Journal Article
• Authors: Les, T.; Markiewicz, T.; Osowski, S.; Jesiotr, M.
• Is Part Of: Expert systems with applications. Volume 137(2019)
• Page Start: 335
• Page End: 342
• Publication Date: 2019-12-15
• Subjects: Cell reconstruction -- Image segmentation -- PatchMatch -- Pattern recognition; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2019.05.031
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: We presented automatic system for reconstructing deformed cells in FISH images of breast cancer. The experiments have confirmed high effectiveness of the method on the tested images. The developed computer program can substitute the human medical expert in this tedious work. Abstract: This paper presents a new image processing and analysis technique for the quality evaluation of cell nuclei to support medical diagnostics in breast cancer. The technique allows cell nuclei that are deformed or overlapped by biological material to be reconstructed. The paper proposes a sensitivity and similarity approach, enriching the PatchMatch correspondence algorithm in accurate cell reconstruction. Its application in reconstruction processes enables accelerated computations and an increased probability of obtaining appropriate segmentation results. The numerical results demonstrate that the developed system allows for automatic and effective cell nuclei reconstruction with an acceptable average area accuracy level above 85% compared with manual human results (assuming manual segmentation as a true value). The reconstruction system allows for the recovery of the proper shape of the analyzed distorted cells very rapidly and in a repeatable manner. An additional advantage of the procedure is that the nuclei area overlapped by artifacts or other cells can be determined. The experimental results prove the high utility of the method in final HER2 gene amplification assessment in breast cancer images.