Un Protocolo Integrado para la Investigación y el Monitoreo de la Leismaniasis Cutánea
(An Integrated Protocol for the Research and Monitoring of Cutaneous Leishmaniasis)
Omar Zenteno (email@example.com)2, Fernando Zvietcovich (firstname.lastname@example.org.)2, Diana Zapata (email@example.com)2, Helena Maruenda (firstname.lastname@example.org)2, Braulio Valencia (email@example.com)1, Alejandro Llanos (firstname.lastname@example.org)1, Jorge Arevalo (email@example.com)1, Maria Montero (firstname.lastname@example.org)2, Roberto Lavarello (email@example.com)2, Benjamin Castañeda (firstname.lastname@example.org)2
1Universidad Peruana Cayetano Heredia2Pontificia Universidad Católica del Perú
This paper appears in: Revista IEEE América Latina
Publication Date: Nov. 2017
Volume: 15, Issue: 11
Cutaneous Leishmaniasis is a skin infection which is commonly present in underdeveloped countries. The incidence is particularly high in amazonic countries of Latin-America like Brazil, Colombia and Perú and is usually reported as endemic. In Perú, more than one million people are at risk of infection and approximately 6,000 new cases are detected each year. The present work proposes to integrate a set of control, monitoring and disease quantification procedures in: (1) an automated tool to expedite the analysis in laboratories studying parasiticidal agents and (2) a non-invasive treatment monitoring protocol. The first, consists in the adaptation of an optical microscope KRUSS MBL3100 to perform a fast image capture and automated promastigotes identification. This may be of value to evaluate the effectiveness of various parasiticidal agents. The counting process is performed by an automatic segmentation in the RGB green color space discriminating elements by their area. The second, proposes a protocol for monitoring the evolution of the disease treatment divided into three stages: supra-skin modeling and reconstruction, subcutaneous exploration by textural characteristics and volumetric segmentation. This protocol is performed using a Next Engine HD 3D scanner and a Vevo Visualsonix 2100 ultrasonic scanner. The results show improvements in sample processing time, accuracy and inter- and intra-operational variability. The sensitivity and accuracy of the microscopic identification system was of 97% and 92% respectively. The exactitude and precision error was up to 2% and the sensitivity and specificity went as high as 71% in the 3D reconstruction and texture analysis respectively.
Leishamaniasis, 3D Reconstruction, Ultrasound Imaging, Texture Analysis, Disease Monitoring.
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