Book chapter
Region-Based Segmentation of Parasites for High-throughput Screening
Advances in Visual Computing, pp.43-53
Lecture Notes in Computer Science, Springer Berlin Heidelberg
2011
DOI: 10.1007/978-3-642-24028-7_5
Abstract
This paper proposes a novel method for segmenting microscope images of schisotsomiasis. Schistosomiasis is a parasitic disease with a global impact second only to malaria. Automated analysis of the parasite’s reaction to drug therapy enables high-throughput drug discovery. These reactions take the form of phenotypic changes that are currently evaluated manually via a researcher viewing the video and assigning phenotypes. The proposed method is capable of handling the unique challenges of this task including the complex set of morphological, appearance-based, motion-based, and behavioral changes of parasites caused by putative drug therapy. This approach adapts a region-based segmentation algorithm designed to quickly identify the background of an image. This modified implementation along with morphological post-processing provides accurate and efficient segmentation results. The results of this algorithm improve the correctness of automated phenotyping and provide promise for high-throughput drug screening.
Details
- Title: Subtitle
- Region-Based Segmentation of Parasites for High-throughput Screening
- Creators
- Asher Moody-Davis - San Francisco State UniversityLaurent Mennillo - Institut de Neurobiologie de la MéditerranéeRahul Singh - San Francisco State University
- Resource Type
- Book chapter
- Publication Details
- Advances in Visual Computing, pp.43-53
- Publisher
- Springer Berlin Heidelberg; Berlin, Heidelberg
- Series
- Lecture Notes in Computer Science
- DOI
- 10.1007/978-3-642-24028-7_5
- eISSN
- 1611-3349
- ISSN
- 0302-9743
- Language
- English
- Date published
- 2011
- Academic Unit
- Computer Science
- Record Identifier
- 9984446529202771
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