Automatic nuclei detection on cytological images using the firefly optimization algorithm

Authors:
Paweł Filipczuk;Weronika Wojtak;Andrzej Obuchowicz
Affiliations:
Institute of Control & Computation Engineering, Zielona Góra, Poland;Faculty of Electrical Engineering, Computer Science and Telecommunications, Zielona Góra, Poland;Institute of Control & Computation Engineering, Zielona Góra, Poland
Venue:
ITIB'12 Proceedings of the Third international conference on Information Technologies in Biomedicine
Year:
2012

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Abstract

The firefly algorithm is a powerful optimization method inspired by the flashing behavior of fireflies. In our work on computer aided breast cancer diagnosis we met a problem of automatic marking of nuclei. Our system is based on analysis of microscopic images of fine needle biopsy material. The task of the system is to identify benign and malignant lesions (optionally it can also distinguish fibroadenoma). For this purpose it extracts nuclei from cytological images in segmentation phase, then it determines their morphometric features and finally classifies the case. Some segmentation methods require a preliminary selection of objects on the image. We have adapted the firefly algorithm to this task. We have also proposed an initialization procedure. The method was experimentally shown to be satisfactorily effective. The approach was tested with real case medical data collected from patients of the Regional Hospital in Zielona Góra.