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High dynamic range shortwave infrared (SWIR) imaging of mice with an InGaAs camera
Amish Patel1,2, Xingjian Zhong1,2, Mallory Moffett2
1Boston University, Department of Biomedical Engineering, Boston, Massachusetts, USA.
Biorxiv : the Preprint Server for Biology
|November 24, 2025
Summary
This study introduces a high dynamic range (HDR) imaging method for shortwave infrared (SWIR) applications, enhancing quantitative fluorescence analysis in preclinical research. The new technique improves imaging across wide intensity ranges, streamlining workflows and maintaining accuracy.
Area of Science:
- Biomedical Imaging
- Optical Engineering
- Preclinical Research
Background:
- Shortwave infrared (SWIR) imaging offers deep tissue penetration and low autofluorescence for preclinical studies.
- InGaAs cameras in SWIR imaging have limited dynamic range, restricting the analysis of both bright and dim fluorescent signals.
- Quantitative fluorescence imaging is crucial for biodistribution studies but is challenged by dynamic range limitations.
Purpose of the Study:
- To develop a high dynamic range (HDR) imaging method for InGaAs detectors in SWIR fluorescence imaging.
- To enable quantitative fluorescence analysis across a wide range of intensities in preclinical models.
- To overcome the limitations of limited dynamic range in current SWIR imaging systems.
Main Methods:
- Adapted classical HDR algorithms for InGaAs detectors, incorporating exposure-time-dependent dark current subtraction.
- Implemented preprocessing steps to remove saturated and noisy pixels before camera response function recovery.
- Utilized dynamic weighting range adjustment to manage intensity variations at longer exposure times.
- Validated the method using indocyanine green and quantum dots in mouse models.
Main Results:
- Achieved a 22 dB improvement in dynamic range compared to single exposures.
- Enabled simultaneous quantification across over three orders of magnitude of fluorophore concentration.
- Demonstrated improved contrast-to-noise ratios and vascular contrast in vivo, while preserving quantitative accuracy.
- Showcased rapid processing of datasets after a single camera calibration.
Conclusions:
- The software-based HDR SWIR imaging approach significantly enhances preclinical imaging workflows.
- Eliminates the need for exposure parameter optimization, allowing comprehensive biodistribution analysis from single acquisitions.
- Preserves quantitative accuracy, making it a valuable tool for drug development and biological research.
