Conference paper
Segmentation and border identification of cells in images of peripheral blood smear slides
30th Australasian Computer Science Conference, ACSC 2007 (Ballarat, Australia, 30/01/2007–02/02/2007)
2007
Abstract
We present an unsupervised blood cell segmentation algorithm for images taken from peripheral blood smear slides. Unlike prior algorithms the method is fast; fully automated; finds all objects-cells, cell groups and cell fragments-that do not intersect the image border; identifies the points interior to each object; finds an accurate one pixel wide border for each object; separates objects that just touch; and has been shown to work with a wide selection of red blood cell morphologies. The full algorithm was tested on two sets of images. In the first set of 47 images, 97.3% of the 2962 image objects were correctly segmented. The second test set-51 images from a different source-contained 5417 objects for which the success rate was 99.0%. The time taken for processing a 2272x1704 image ranged from 4.86 to 11.02 seconds on a Pentium 4, 2.4 GHz machine, depending on the number of objects in the image.
Details
- Title
- Segmentation and border identification of cells in images of peripheral blood smear slides
- Authors/Creators
- N. Ritter (Author/Creator)J. Cooper (Author/Creator)
- Conference
- 30th Australasian Computer Science Conference, ACSC 2007 (Ballarat, Australia, 30/01/2007–02/02/2007)
- Identifiers
- 991005542547507891
- Murdoch Affiliation
- School of Information Technology
- Language
- English
- Resource Type
- Conference paper
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