Journal article
Segmenting the Etiological Agent of Schistosomiasis for High-Content Screening
IEEE transactions on medical imaging, Vol.32(6), pp.1007-1018
06/01/2013
DOI: 10.1109/TMI.2013.2247412
PMID: 23428618
Abstract
Schistosomiasis is a parasitic disease with a global health impact second only to malaria. The World Health Organization has classified schistosomiasis as an illness for which new therapies are urgently needed. However, the causative parasite is refractory to current high-throughput drug screening due to the diversity and complexity of shape, appearance and movement-based phenotypes exhibited in response to putative drugs. Currently, there is no automated image-based approach capable of relieving this deficiency. We propose and validate an image segmentation algorithm designed to overcome the distinct challenges posed by schistosomes and macroparasites in general, including irregular shapes and sizes, dense groups of touching parasites and the unpredictable effects of drug exposure. Our approach combines a region-based distributing function with a novel edge detector derived from phase congruency and grayscale thinning by threshold superposition. The method is sufficiently rapid, robust and accurate to be used for quantitative analysis of diverse parasite phenotypes in high-throughput and high-content screening.
Details
- Title: Subtitle
- Segmenting the Etiological Agent of Schistosomiasis for High-Content Screening
- Creators
- Daniel E. Asarnow - San Francisco State UniversityRahul Singh - San Francisco State University
- Resource Type
- Journal article
- Publication Details
- IEEE transactions on medical imaging, Vol.32(6), pp.1007-1018
- DOI
- 10.1109/TMI.2013.2247412
- PMID
- 23428618
- NLM abbreviation
- IEEE Trans Med Imaging
- ISSN
- 0278-0062
- eISSN
- 1558-254X
- Publisher
- Institute of Electrical and Electronics Engineers
- Number of pages
- 12
- Grant note
- R01AI089896 / NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID) 1R01AI089896 / National Institutes of Health, National Institute of Allergy and Infectious Diseases (NIH-NIAID); United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID) IIS-0644418 / National Science Foundation (NSF) California State University Program for Research and Education in Biotechnology (CSUPERB)
- Language
- English
- Date published
- 06/01/2013
- Academic Unit
- Computer Science
- Record Identifier
- 9984455943302771
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