Active contours for overlapping cervical cell segmentation

التفاصيل البيبلوغرافية
العنوان: Active contours for overlapping cervical cell segmentation
المؤلفون: Flávio H. D. Araújo, Fátima N. S. de Medeiros, Romuere R. V. Silva, Paulo H. C. Oliveira, Jeova F. S. Rocha Neto, Andrea Gomes Campos Bianchi, Daniela Ushizima
المصدر: International Journal of Biomedical Engineering and Technology. 35:70
بيانات النشر: Inderscience Publishers, 2021.
سنة النشر: 2021
مصطلحات موضوعية: 0303 health sciences, Active contour model, 010504 meteorology & atmospheric sciences, Computer science, business.industry, Biomedical Engineering, Pattern recognition, Cervical cells, Mass segmentation, 01 natural sciences, Cervical cell, Clinical Practice, 03 medical and health sciences, medicine.anatomical_structure, Cytoplasm, medicine, Segmentation, Artificial intelligence, business, Nucleus, 030304 developmental biology, 0105 earth and related environmental sciences
الوصف: The nuclei and cytoplasm segmentation of cervical cells is a well studied problem. However, the current segmentation algorithms are not robust to clinical practice due to the high computational cost or because they cannot accurately segment cells with high overlapping. In this paper, we propose a method that is capable of segmenting both cytoplasm and nucleus of each individual cell in a clump of overlapping cells. The proposed method consists of three steps: 1) cellular mass segmentation; 2) nucleus segmentation; 3) cytoplasm identification based on an active contour method. We carried out experiments on both synthetic and real cell images. The performance evaluation of the proposed method showed that it was less sensitive to the increase in the number of cells per image and the overlapping ratio against two other existing algorithms. It has also achieved a promising low processing time and, hence, it has the potential to support expert systems for cervical cell recognition.
تدمد: 1752-6426
1752-6418
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1d9bd94519cc21937b0bd8de9eade448
https://doi.org/10.1504/ijbet.2021.10035163
رقم الأكسشن: edsair.doi.dedup.....1d9bd94519cc21937b0bd8de9eade448
قاعدة البيانات: OpenAIRE