A Nuclei Segmentation Method Based on Butterfly Algorithm for H& Estained Images
Venubabu Rachapudi1, G. Lavanya Devi2, N. Sai Chaitanya3
1Venubabu Rachapudi, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
2G. Lavanya Devi, Department of Computer Science and Systems Engineering, AUCE(A), Andhra University, Visakhapatnam (Andhra Pradesh), India.
3N. Sai Chaitanya, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
Manuscript received on 18 April 2019 | Revised Manuscript received on 25 April 2019 | Manuscript published on 30 April 2019 | PP: 860-864 | Volume-8 Issue-4, April 2019 | Retrieval Number: D6445048419/19©BEIESP
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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: Nuclei segmentation in H&E strained images plays a vital role in diagnosis of various diseases. Huge research is being carried out by various researchers in developing computerized methods for automatic segmentation of nuclei. These computerized methods played vital role in minimizing human intervention in diagnosis of various diseases. In this paper, we have proposed a new nuclei segmentation method which uses Butterfly Algorithm for avoiding local optima for Histopathological images. The algorithm is based on food foraging strategy of butterflies, as they use their sense of sight, taste, smell, touch and hearing to determine the position of food and mating partner. Histopathological images data set of TNBC patients has been taken. The performance measure of the proposed method is evaluated bases on Accuracy, F1 score and Aggregated Jaccard Index
Keywords: Butterfly Algorithm, Histopathological Images, Nuclei Segmentation.
Scope of the Article: Image Processing