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Proceedings Paper

New features for detecting cervical precancer using hyperspectral diagnostic imaging
Author(s): Gordon S. Okimoto; Mary F. Parker; Gregory C. Mooradian; Steven J. Saggese; Ames A. Grisanti; Dennis M. O'Connor; Kunio Miyazawa
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Paper Abstract

Principal component analysis (PCA) in the wavelet domain provides powerful new features for the non-invasive detection of cervical intraepithelial neoplasia (CIN) using fluorescence imaging spectroscopy. These features are known as principal wavelet components (PWCs). The multiscale structure of the fluorescence spectrum for each pixel of the hyperspectral data cube is extracted using the continuous wavelet transform. PCA is then used to compress and denoise the wavelet representation for presentation to a feed- forward neural network for tissue classification. Using PWC features as inputs to a 5-class NN resulted in average correct classification rates of 95% over five cervical tissue classes corresponding to low-grade dysplasia, squamous, columnar, metaplasia plus a fifth class for other unspecified tissue types, blood and mucus. A 2-class NN was also trained to discriminate between CIN1 and normal tissue with sensitivity and specificity of 98% and 99%, respectively. All performance assessments were based on test data from a set of patients not seen during NN training. Trained neural classifiers were used to `compress' and transform 3D hyperspectral data cubes into 2D color-coded images that accurately mapped the spatial distribution of both normal and dysplastic tissue over the surface of the entire cervix.

Paper Details

Date Published: 22 May 2001
PDF: 13 pages
Proc. SPIE 4255, Clinical Diagnostic Systems, (22 May 2001); doi: 10.1117/12.426747
Show Author Affiliations
Gordon S. Okimoto, Trex Enterprises, Inc. (United States)
Mary F. Parker, Walter Reed Army Medical Ctr. (United States)
Gregory C. Mooradian, Science and Engineering Associates, Inc. (United States)
Steven J. Saggese, Science and Engineering Associates, Inc. (United States)
Ames A. Grisanti, Science and Engineering Associates, Inc. (United States)
Dennis M. O'Connor, Clinical Pathology Associates (United States)
Kunio Miyazawa, Tripler Army Medical Ctr. (United States)


Published in SPIE Proceedings Vol. 4255:
Clinical Diagnostic Systems
Gerald E. Cohn, Editor(s)

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