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Proceedings Paper

Early-stage tumor detection using photoacoustic microscopy: a pattern recognition approach
Author(s): Chenghung Yeh; Liang Wang; Jinyang Liang; Yong Zhou; Song Hu; Rebecca E. Sohn; Jeffrey M. Arbeit; Lihong V. Wang
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Paper Abstract

We report photoacoustic microscopy (PAM) of arteriovenous (AV) shunts in early stage tumors in vivo, and develop a pattern recognition framework for computerized tumor detection. Here, using a high-resolution photoacoustic microscope, we implement a new blood oxygenation (sO2)-based disease marker induced by the AV shunt effect in tumor angiogenesis. We discovered a striking biological phenomenon: There can be two dramatically different sO2 values in bloodstreams flowing side-by-side in a single vessel. By tracing abnormal sO2 values in the blood vessels, we can identify a tumor region at an early stage. To further automate tumor detection based on our findings, we adopt widely used pattern recognition methods and develop an efficient computerized classification framework. The test result shows over 80% averaged detection accuracy with false positive contributing 18.52% of error test samples on a 50 PAM image dataset.

Paper Details

Date Published: 3 March 2017
PDF: 9 pages
Proc. SPIE 10064, Photons Plus Ultrasound: Imaging and Sensing 2017, 100644N (3 March 2017); doi: 10.1117/12.2253529
Show Author Affiliations
Chenghung Yeh, Washington Univ. in St. Louis (United States)
Liang Wang, Washington Univ. in St. Louis (United States)
Jinyang Liang, Washington Univ. in St. Louis (United States)
Yong Zhou, Washington Univ. in St. Louis (United States)
Song Hu, Univ. of Virginia (United States)
Rebecca E. Sohn, Washington Univ. School of Medicine in St. Louis (United States)
Jeffrey M. Arbeit, Washington Univ. School of Medicine in St. Louis (United States)
Lihong V. Wang, Washington Univ. in St. Louis (United States)


Published in SPIE Proceedings Vol. 10064:
Photons Plus Ultrasound: Imaging and Sensing 2017
Alexander A. Oraevsky; Lihong V. Wang, Editor(s)

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