Three-dimensional NIR-II tumor blood vessels and bone imaging using rotational stereo vision in small animals

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Optical imaging in the second near-infrared (NIR-II, 1000-1700 nm) is suitable for visualizing tumor vascular imaging and targeting bone structures in small animals. In this study, we developed a novel three-dimensional (3D) NIR-II fluorescence rotational stereo imaging system for conducting 3D tumor vascular imaging and bone imaging in mice with only one NIR-II camera and a rotational stereo vision technique. Our system utilizes a 3D blood vessel reconstruction algorithm to present high-resolution 3D blood vessel maps and skeletal systems through two camera views. This technique allows for the visualization of bone structure and the identification of metabolic diseases such as osteoporosis. We validated the system with custom-made 3D printing phantoms and 4T1 tumor-bearing mice, demonstrating the ability to accurately recover the tumor blood vessels and bones with an imaging depth of 5 mm, an image resolution of 0.15 mm, and a depth resolution of 0.35 mm. This pioneering development provides an effective tool for non-invasive real-time NIR-II fluorescence imaging and is instrumental in understanding the effects of cancer treatments on tumor vessels and bone structure in small animals.

Original languageEnglish
Title of host publicationDiffuse Optical Spectroscopy and Imaging IX
EditorsDavide Contini, Yoko Hoshi, Thomas D. O'Sullivan
ISBN (Electronic)9781510664654
StatePublished - 2023
EventDiffuse Optical Spectroscopy and Imaging IX 2023 - Munich, Germany
Duration: 25 Jun 202328 Jun 2023

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


ConferenceDiffuse Optical Spectroscopy and Imaging IX 2023


  • 3D
  • blood vessels imaging
  • bone imaging
  • NIR-II
  • Polymer dots
  • rotational stereo imaging
  • tumor imaging


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