Abstract
In this paper we study automatic classification of working areas in peripheral blood smears using image analysis and recognition methods. Such automatic classification can provide objective and reproducible quality control for the evaluation of smears and smear maker devices. However, research in this filed has drawn little attention. Existing methods either can not differentiate correctly different cell distributions or rely on the extraction of the central pallor zones in cells for counting, which are not always observable. In contrast, we do not rely on the pallor zone extraction thus on more general basis. We introduce two generic parameters to measure the goodness of working areas, one for the degree of overlap, and the other for the spatial occupancy. We also propose a cascading classification network for the classification of different areas. The effectiveness of our method has been tested on over 150 labeled images acquired from three malaria-infected Giemsa-stained blood smears using an oil immersion 100x objective.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 |
| Publisher | IEEE Computer Society |
| Pages | 4074-4077 |
| Number of pages | 4 |
| ISBN (Print) | 9781424418152 |
| DOIs | |
| Publication status | Published - 2008 |
| Externally published | Yes |
| Event | 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada Duration: 20 Aug 2008 → 25 Aug 2008 |
Publication series
| Name | Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology" |
|---|
Conference
| Conference | 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 |
|---|---|
| Country/Territory | Canada |
| City | Vancouver, BC |
| Period | 20/08/08 → 25/08/08 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Free Keywords
- Central pallor zone
- Classification
- Distribution
- Equivalent diameter
- Generic features
- Occupancy
- Overlap
- Peripheral blood smears
- Working area
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Signal Processing
- Biomedical Engineering
- Health Informatics
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