Non-invasive tumor detection using NIR light

Yung Chi Lin, Sheng Hao Tseng, Pau Choo Chung, Ching Fang Yang, Ming Han Wu, Shoko Nioka, Yong Kie Wong

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper presents a non-invasive device with near-infrared (NIR) light for the analysis of tissue components, particularly the blood oxygen saturation and hemoglobin concentration, by using photon diffusion equation. The device equips with a multispectral (7 wavelengths) LED and multiple sensors of different spatial distances to the LED source. An optimal fitting of the measurement data obtained from these sensors is employed to achieve a more accurate estimation of the concentrations of tissue components, such as hemoglobin, water, and lipid of tissue samples, which are often referred in clinic diagnosis. Besides, Monte Carlo simulation is applied to analyze how photons transmit in tissue under different depth levels. According to the simulation results, the proposal introduces a method for tumor detection to reduce the effect of shallow layer and to increase detection accuracy for deep layer tumors. The device was also evaluated by phantoms and clinical data acquired from the patients with neck tumors. Results indicate that our device is not only sensitive to the presence of neck tumors but also can be applied to study other clinical diseases.

Original languageEnglish
Title of host publication2013 IEEE Biomedical Circuits and Systems Conference, BioCAS 2013
Number of pages4
Publication statusPublished - 2013
Event2013 IEEE Biomedical Circuits and Systems Conference, BioCAS 2013 - Rotterdam, Netherlands
Duration: 2013 Oct 312013 Nov 2

Publication series

Name2013 IEEE Biomedical Circuits and Systems Conference, BioCAS 2013


Other2013 IEEE Biomedical Circuits and Systems Conference, BioCAS 2013

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Biomedical Engineering
  • Electrical and Electronic Engineering


Dive into the research topics of 'Non-invasive tumor detection using NIR light'. Together they form a unique fingerprint.

Cite this