Optical imaging of breast tumor through temporal log-slope difference mappings

Zhixiong Guo, Siew Kan Wan, David A. August, Jinpin Ying, Stanley M. Dunn, John L. Semmlow

Research output: Contribution to journalArticlepeer-review

41 Scopus citations


A novel optical temporal log-slope difference mapping approach is proposed for cancerous breast tumor detection. In this method, target tissues are illuminated by near-infrared (700-1000 nm) ultrashort laser pulses from various surface source points, and backscattered time-resolved light signals are collected at the same surface points. By analyzing the log-slopes of decaying signals over all points on the source-detection grid, a log-slope distribution on the 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 breast tumors in two model tissue phantoms through computer simulation. The first model has a spherical tumor of 6 mm in diameter embedded at the tissue center. The second model is a large tissue phantom embedded with a non-centered spherical tumor 8 mm in diameter. Monte Carlo methods were employed to simulate the light transport and signal measurement. It is shown that the tumor in both the tissue models will 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.

Original languageEnglish (US)
Pages (from-to)209-223
Number of pages15
JournalComputers in Biology and Medicine
Issue number2
StatePublished - Feb 2006

All Science Journal Classification (ASJC) codes

  • Health Informatics
  • Computer Science Applications


  • Absorption contrast agent
  • Breast cancer detection
  • Monte Carlo method
  • Near-infrared imaging
  • Simulation
  • Temporal log-slope
  • Ultrafast laser


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