Mobile Hardware Based Implementation of a Novel, Efficient, Fuzzy Logic Inspired Edge Detection Technique for Analysis of Malaria Infected Microscopic Thin Blood Images
- Submitting institution
-
The University of Westminster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- q9596
- Type
- D - Journal article
- DOI
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10.1016/j.procs.2018.10.187
- Title of journal
- Procedia Computer Science
- Article number
- -
- First page
- 390
- Volume
- 141
- Issue
- -
- ISSN
- 1877-0509
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper describes a novel, variably sensitive edge detection algorithm for object identification in even low-quality thin blood smear images. The research is significant as it has the potential to offer a fast and reliable mass monitoring and analytical tool for clinical pathology. It has high relevance and potential for extended applications on blood borne disease and parasitic infection diagnosis and the subsequent eradication in endemic regions. This research has been the foundation of multiple research projects in recent years, including the University of Westminster’s Developing Researcher Grant funded Neglected Tropical Disease diagnosis project in 2020.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
