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Synthetic white balancing for intra-operative hyperspectral imaging


Bahl, Anisha; Horgan, Conor C; Janatka, Mirek; MacCormac, Oscar J; Noonan, Philip; Xie, Yijing; Qiu, Jianrong; Cavalcanti, Nicola; Fürnstahl, Philipp; Ebner, Michael; Bergholt, Mads S; Shapey, Jonathan; Vercauteren, Tom (2023). Synthetic white balancing for intra-operative hyperspectral imaging. Journal of Medical Imaging, 10(4):046001.

Abstract

PURPOSE

Hyperspectral imaging shows promise for surgical applications to non-invasively provide spatially resolved, spectral information. For calibration purposes, a white reference image of a highly reflective Lambertian surface should be obtained under the same imaging conditions. Standard white references are not sterilizable and so are unsuitable for surgical environments. We demonstrate the necessity for in situ white references and address this by proposing a novel, sterile, synthetic reference construction algorithm.

APPROACH

The use of references obtained at different distances and lighting conditions to the subject were examined. Spectral and color reconstructions were compared with standard measurements qualitatively and quantitatively, using and normalized RMSE, respectively. The algorithm forms a composite image from a video of a standard sterile ruler, whose imperfect reflectivity is compensated for. The reference is modeled as the product of independent spatial and spectral components, and a scalar factor accounting for gain, exposure, and light intensity. Evaluation of synthetic references against ideal but non-sterile references is performed using the same metrics alongside pixel-by-pixel errors. Finally, intraoperative integration is assessed though cadaveric experiments.

RESULTS

Improper white balancing leads to increases in all quantitative and qualitative errors. Synthetic references achieve median pixel-by-pixel errors lower than 6.5% and produce similar reconstructions and errors to an ideal reference. The algorithm integrated well into surgical workflow, achieving median pixel-by-pixel errors of 4.77% while maintaining good spectral and color reconstruction.

CONCLUSIONS

We demonstrate the importance of in situ white referencing and present a novel synthetic referencing algorithm. This algorithm is suitable for surgery while maintaining the quality of classical data reconstruction.

Abstract

PURPOSE

Hyperspectral imaging shows promise for surgical applications to non-invasively provide spatially resolved, spectral information. For calibration purposes, a white reference image of a highly reflective Lambertian surface should be obtained under the same imaging conditions. Standard white references are not sterilizable and so are unsuitable for surgical environments. We demonstrate the necessity for in situ white references and address this by proposing a novel, sterile, synthetic reference construction algorithm.

APPROACH

The use of references obtained at different distances and lighting conditions to the subject were examined. Spectral and color reconstructions were compared with standard measurements qualitatively and quantitatively, using and normalized RMSE, respectively. The algorithm forms a composite image from a video of a standard sterile ruler, whose imperfect reflectivity is compensated for. The reference is modeled as the product of independent spatial and spectral components, and a scalar factor accounting for gain, exposure, and light intensity. Evaluation of synthetic references against ideal but non-sterile references is performed using the same metrics alongside pixel-by-pixel errors. Finally, intraoperative integration is assessed though cadaveric experiments.

RESULTS

Improper white balancing leads to increases in all quantitative and qualitative errors. Synthetic references achieve median pixel-by-pixel errors lower than 6.5% and produce similar reconstructions and errors to an ideal reference. The algorithm integrated well into surgical workflow, achieving median pixel-by-pixel errors of 4.77% while maintaining good spectral and color reconstruction.

CONCLUSIONS

We demonstrate the importance of in situ white referencing and present a novel synthetic referencing algorithm. This algorithm is suitable for surgery while maintaining the quality of classical data reconstruction.

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3 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Balgrist University Hospital, Swiss Spinal Cord Injury Center
04 Faculty of Medicine > Institute of Molecular Cancer Research
07 Faculty of Science > Institute of Molecular Cancer Research
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Language:English
Date:24 July 2023
Deposited On:07 Sep 2023 12:01
Last Modified:29 Jun 2024 01:38
Publisher:S P I E - International Society for Optical Engineering
ISSN:2329-4302
OA Status:Closed
Publisher DOI:https://doi.org/10.1117/1.JMI.10.4.046001
PubMed ID:37492187
Other Identification Number:PMCID: PMC10363486