Conference proceeding
Classification of layered tissue phantoms for detection of changes in epithelial tissue below the surface using a Stochastic Decomposition Model for scattered signal
2008 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, VOLS 1-4, pp 1211-1214
01 Jan 2008
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This paper answers the question of whether it is possible to detect changes inside epithelium layered structures using a Stochastic Decomposition Method (SDM) [1, 2] that models the scattered light reflected from the layered structure over an area ( 2-D scan) illuminated by an optical sensor (fiber) emitting light at either one wavelength or with white light. Our technique correlates the differential changes in the reflected tissue texture with the morphological and physical changes that occur in the tissue occurring below the surface of the structure. This work has great potential in detecting changes in mucosal structures and may lead to enhanced endoscopy when the disease is developing to the below the surface and hence becoming hidden during colonoscopy or endoscopic examination. Tests are performed on layered tissue phantoms and the results obtained show great effectiveness of the model and method in picking up changes in the morphology of the layered tissue phantoms occurring below the surface (greater than 0.6mm deep).
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Details
- Title
- Classification of layered tissue phantoms for detection of changes in epithelial tissue below the surface using a Stochastic Decomposition Model for scattered signal
- Creators
- Fernand S. Cohen - Drexel UniversityEzgi Taslidere - Drexel UniversitySreekant Murthy - Drexel UniversityIEEE
- Publication Details
- 2008 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, VOLS 1-4, pp 1211-1214
- 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:000258259800304
- Scopus ID
- 2-s2.0-51049105478
- Other Identifier
- 991019168271604721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Engineering, Biomedical
- Engineering, Electrical & Electronic
- Imaging Science & Photographic Technology
- Nanoscience & Nanotechnology