Conference proceeding
Feature extraction and segmentation in medical images by statistical optimization and point operation approaches
Proceedings of SPIE, Vol.5032(1), pp.1676-1684
Medical Imaging 2003: Image Processing
05/16/2003
DOI: 10.1117/12.481154
Abstract
Feature extraction is a critical preprocessing step, which influences the outcome of the entire process of developing significant metrics for medical image evaluation. The purpose of this paper is firstly to compare the effect of an optimized statistical feature extraction methodology to a well designed combination of point operations for feature extraction at the preprocessing stage of retinal images for developing useful diagnostic metrics for retinal diseases such as glaucoma and diabetic retinopathy. Segmentation of the extracted features allow us to investigate the effect of occlusion induced by these features on generating stereo disparity mapping and 3-D visualization of the optic cup/disc. Segmentation of blood vessels in the retina also has significant application in generating precise vessel diameter metrics in vascular diseases such as hypertension and diabetic retinopathy for monitoring progression of retinal diseases.
Details
- Title: Subtitle
- Feature extraction and segmentation in medical images by statistical optimization and point operation approaches
- Creators
- Shuyu Yang - Texas Tech UniversityPhilip King - Texas Tech UniversityEnrique Corona - Texas Tech UniversityMark P Wilson - Texas Tech UniversityKaan Aydin - Texas Tech UniversitySunanda Mitra - Texas Tech UniversityPeter Soliz - Kestrel Corp. (United States)Brian S Nutter - Texas Tech UniversityYoung H Kwon - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.5032(1), pp.1676-1684
- Conference
- Medical Imaging 2003: Image Processing
- DOI
- 10.1117/12.481154
- ISSN
- 0277-786X
- Language
- English
- Date published
- 05/16/2003
- Academic Unit
- Ophthalmology and Visual Sciences
- Record Identifier
- 9984182970802771
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