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Proceedings Paper

Quantification of photoacoustic microscopy images for ovarian cancer detection
Author(s): Tianheng Wang; Yi Yang; Umar Alqasemi; Patrick D. Kumavor; Xiaohong Wang; Melinda Sanders; Molly Brewer; Quing Zhu
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Paper Abstract

In this paper, human ovarian tissues with malignant and benign features were imaged ex vivo by using an opticalresolution photoacoustic microscopy (OR-PAM) system. Several features were quantitatively extracted from PAM images to describe photoacoustic signal distributions and fluctuations. 106 PAM images from 18 human ovaries were classified by applying those extracted features to a logistic prediction model. 57 images from 9 ovaries were used as a training set to train the logistic model, and 49 images from another 9 ovaries were used to test our prediction model. We assumed that if one image from one malignant ovary was classified as malignant, it is sufficient to classify this ovary as malignant. For the training set, we achieved 100% sensitivity and 83.3% specificity; for testing set, we achieved 100% sensitivity and 66.7% specificity. These preliminary results demonstrate that PAM could be extremely valuable in assisting and guiding surgeons for in vivo evaluation of ovarian tissue.

Paper Details

Date Published: 3 March 2014
PDF: 6 pages
Proc. SPIE 8943, Photons Plus Ultrasound: Imaging and Sensing 2014, 894306 (3 March 2014); doi: 10.1117/12.2036129
Show Author Affiliations
Tianheng Wang, Univ. of Connecticut (United States)
Yi Yang, Univ. of Connecticut (United States)
Umar Alqasemi, Univ. of Connecticut (United States)
Patrick D. Kumavor, Univ. of Connecticut (United States)
Xiaohong Wang, Univ. of Connecticut Health Ctr. (United States)
Melinda Sanders, Univ. of Connecticut Health Ctr. (United States)
Molly Brewer, Univ. of Connecticut Health Ctr. (United States)
Quing Zhu, Univ. of Connecticut (United States)


Published in SPIE Proceedings Vol. 8943:
Photons Plus Ultrasound: Imaging and Sensing 2014
Alexander A. Oraevsky; Lihong V. Wang, Editor(s)

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