Paper
7 December 2004 Noninvasive imaging of tumors using temporal log-slope difference mappings
Zhixiong Guo, Siew Kan Wan, David A. August, Jinpin Ying, Stanley M. Dunn, John L. Semmlow
Author Affiliations +
Proceedings Volume 5588, Smart Medical and Biomedical Sensor Technology II; (2004) https://doi.org/10.1117/12.571317
Event: Optics East, 2004, Philadelphia, Pennsylvania, United States
Abstract
An optical temporal log-slope difference mapping approach is proposed for cancerous tumor detection; in which target tissues are illuminated by near-infrared ultrashort laser pulses, and backscattered time-resolved light signals are collected. By analyzing the log-slopes of the temporally decaying signals, a log-slope distribution on the detection surface is obtained. After administration of absorption contrast agents, the presence of cancerous tumors increases the decaying steepness of the transient signals. The mapping of log-slope difference between native tissue and absorption-enhanced cancerous tissue indicates the location and projection of tumors on the detection surface. In this paper, we examine this method in the detection of tumor inside a model tissue through Monte Carlo simulation. The tissue model has a spherical tumor of different sizes embedded at the tissue center. It is found that tumors with size not less than 4 mm in diameter in the tissue model can be accurately projected on the detection surface by the proposed log-slope difference mapping method. The image processing is very fast and does not require any inverse optimization in image reconstruction. Parametric studies are conducted to examine to the influences of absorption contrast, tumor size and depth.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhixiong Guo, Siew Kan Wan, David A. August, Jinpin Ying, Stanley M. Dunn, and John L. Semmlow "Noninvasive imaging of tumors using temporal log-slope difference mappings", Proc. SPIE 5588, Smart Medical and Biomedical Sensor Technology II, (7 December 2004); https://doi.org/10.1117/12.571317
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KEYWORDS
Tumors

Tissues

Absorption

Natural surfaces

Signal detection

Monte Carlo methods

Optical properties

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