Automatic Segmentation of Leishmania Parasite in Microscopic Images Using a Modified Cv Level Set Method

Automatic Segmentation of Leishmania Parasite in Microscopic Images Using a Modified Cv Level Set Method Publisher

Farahi M¹ ; Rabbani H¹ ; Talebi A² ; Sarrafzadeh O¹ ; Ensafi S³

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1. Biomedical Engineering Dept., Faculty of Advanced Medical Technology, Isfahan University of Medical Sciences, Isfahan, Iran
2. Pathology Dept., School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
3. Electrical and Computer Engineering Dept., National University of Singapore, Singapore, Singapore

Source: Proceedings of SPIE - The International Society for Optical Engineering Published:2015

Abstract

Visceral Leishmaniasis is a parasitic disease that affects liver, spleen and bone marrow. According to World Health Organization report, definitive diagnosis is possible just by direct observation of the Leishman body in the microscopic image taken from bone marrow samples. We utilize morphological and CV level set method to segment Leishman bodies in digital color microscopic images captured from bone marrow samples. Linear contrast stretching method is used for image enhancement and morphological method is applied to determine the parasite regions and wipe up unwanted objects. Modified global and local CV level set methods are proposed for segmentation and a shape based stopping factor is used to hasten the algorithm. Manual segmentation is considered as ground truth to evaluate the proposed method. This method is tested on 28 samples and achieved 10.90% mean of segmentation error for global model and 9.76% for local model. © 2015 SPIE.

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Ardeshir Talebi (6)

Hossein Rabbani (6)

Style	Citing Format
MLA	Farahi M, et al.. "Automatic Segmentation of Leishmania Parasite in Microscopic Images Using a Modified Cv Level Set Method." Proceedings of SPIE - The International Society for Optical Engineering, vol. 9817, no. , 2015, pp. -.
APA	Farahi M, Rabbani H, Talebi A, Sarrafzadeh O, Ensafi S (2015). Automatic Segmentation of Leishmania Parasite in Microscopic Images Using a Modified Cv Level Set Method. Proceedings of SPIE - The International Society for Optical Engineering, 9817(), -.
Chicago	Farahi M, Rabbani H, Talebi A, Sarrafzadeh O, Ensafi S. "Automatic Segmentation of Leishmania Parasite in Microscopic Images Using a Modified Cv Level Set Method." Proceedings of SPIE - The International Society for Optical Engineering 9817, no. (2015): -.
Harvard	Farahi M et al. (2015) 'Automatic Segmentation of Leishmania Parasite in Microscopic Images Using a Modified Cv Level Set Method', Proceedings of SPIE - The International Society for Optical Engineering, 9817(), pp. -.
Vancouver	Farahi M, Rabbani H, Talebi A, Sarrafzadeh O, Ensafi S. Automatic Segmentation of Leishmania Parasite in Microscopic Images Using a Modified Cv Level Set Method. Proceedings of SPIE - The International Society for Optical Engineering. 2015;9817():-.
BibTex	@article{ author = {Farahi M and Rabbani H and Talebi A and Sarrafzadeh O and Ensafi S}, title = {Automatic Segmentation of Leishmania Parasite in Microscopic Images Using a Modified Cv Level Set Method}, journal = {Proceedings of SPIE - The International Society for Optical Engineering}, volume = {9817}, number = {}, pages = {-}, year = {2015} }
RIS	TY - JOUR AU - Farahi M AU - Rabbani H AU - Talebi A AU - Sarrafzadeh O AU - Ensafi S TI - Automatic Segmentation of Leishmania Parasite in Microscopic Images Using a Modified Cv Level Set Method JO - Proceedings of SPIE - The International Society for Optical Engineering VL - 9817 IS - SP - EP - PY - 2015 ER -

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