Conference proceeding
Tissue characterization and detection of dysplasia using scattered light
2006 3RD IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: MACRO TO NANO, VOLS 1-3, v 3, pp 590-593
01 Jan 2006
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
In this paper, the structural parameters of dysplasia formation in the epithelial tissue are estimated using a stochastic decomposition algorithm (SDM) by means of scattered light. We extract texture parameters obtained from the decomposition that capture the signature of dysplasia formation. These parameters include the number and mean energy of coherent scatterers; deviation from Rayleigh scattering; average energy of diffuse scatterers; and normalized correlation coefficient. The tests are performed on simulations, and tissue-mimicking phantom data. The simulations are based on the light scattered from the cells with varying parameters such as, index of refraction, number of cells, and size of cells. The obtained results demonstrate the proof-of-concept in being able to differentiate between tissue structures that give rise to changes in cell morphology as well as other physical properties such as change in index of refraction. Fusing all the estimated parameter set together results in the differentiation performance (Az value) up to 1(perfect detection) for simulated data, and Az > 0.927 for the phantom data.
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Details
- Title
- Tissue characterization and detection of dysplasia using scattered light
- Creators
- Fernand S. Cohen - Drexel UniversityEzgi Taslidere - Drexel UniversityDilip S. Hari - Drexel UniversityIEEE
- Publication Details
- 2006 3RD IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: MACRO TO NANO, VOLS 1-3, v 3, pp 590-593
- Series
- IEEE International Symposium on Biomedical Imaging
- Publisher
- IEEE
- Number of pages
- 2
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000244446000149
- Scopus ID
- 2-s2.0-33750936231
- Other Identifier
- 991019170474804721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Imaging Science & Photographic Technology
- Radiology, Nuclear Medicine & Medical Imaging