Noncontact 3-D Speckle Contrast Diffuse Correlation Tomography of Tissue Blood Flow Distribution

Chong Huang, Daniel Irwin, Mingjun Zhao, Yu Shang, Nneamaka Agochukwu, Lesley Wong, Guoqiang Yu

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


Recent advancements in near-infrared diffuse correlation techniques and instrumentation have opened the path for versatile deep tissue microvasculature blood flow imaging systems. Despite this progress there remains a need for a completely noncontact, noninvasive device with high translatability from small/testing (animal) to large/target (human) subjects with trivial application on both. Accordingly, we discuss our newly developed setup which meets this demand, termed noncontact speckle contrast diffuse correlation tomography (nc-scDCT). The nc-scDCT provides fast, continuous, portable, noninvasive, and inexpensive acquisition of 3-D tomographic deep (up to 10 mm) tissue blood flow distributions with straightforward design and customization. The features presented include a finite-element-method implementation for incorporating complex tissue boundaries, fully noncontact hardware for avoiding tissue compression and interactions, rapid data collection with a diffuse speckle contrast method, reflectance-based design promoting experimental translation, extensibility to related techniques, and robust adjustable source and detector patterns and density for high resolution measurement with flexible regions of interest enabling unique application-specific setups. Validation is shown in the detection and characterization of both high and low contrasts in flow relative to the background using tissue phantoms with a pump-connected tube (high) and phantom spheres (low). Furthermore, in vivo validation of extracting spatiotemporal 3-D blood flow distributions and hyperemic response during forearm cuff occlusion is demonstrated. Finally, the success of instrument feasibility in clinical use is examined through the intraoperative imaging of mastectomy skin flap.

Original languageEnglish
Article number7934412
Pages (from-to)2068-2076
Number of pages9
JournalIEEE Transactions on Medical Imaging
Issue number10
StatePublished - Oct 2017

Bibliographical note

Funding Information:
Manuscript received April 3, 2017; revised May 18, 2017; accepted May 23, 2017. Date of publication May 26, 2017; date of current version September 29, 2017. The work of L. Wong was supported by the National Endowment for Plastic Surgery under Grant 3048112770. The work of G. Yu was supported in part by the National Institutes of Health under Grant R01-CA149274 and Grant R21-AR062356 and in part by the American Heart Association through Grant-In-Aid under Grant 16GRNT30820006. (Corresponding author: G. Yu.) C. Huang, D. Irwin, M. Zhao, and G. Yu are with the Department of Biomedical Engineering, University of Kentucky, Lexington, KY 40506 USA (e-mail:

Publisher Copyright:
© 1982-2012 IEEE.


  • Finite element modeling
  • image reconstruction-iterative methods
  • optical imaging
  • perfusion imaging
  • system design

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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