A Data Self-Calibration Method Based on High-Density Parallel Plate Diffuse Optical Tomography for Breast Cancer Imaging

When performing the diffuse optical tomography (DOT) of the breast, the mismatch between the forward model and the experimental conditions will significantly hinder the reconstruction accuracy. Therefore, the reference measurement is commonly used to calibrate the measured data before the reconstruc...

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Published inFrontiers in oncology Vol. 11; p. 786289
Main Authors Wang, Xin, Hu, Rui, Wang, Yirong, Yan, Qiang, Wang, Yihan, Kang, Fei, Zhu, Shouping
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 21.12.2021
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ISSN2234-943X
2234-943X
DOI10.3389/fonc.2021.786289

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Summary:When performing the diffuse optical tomography (DOT) of the breast, the mismatch between the forward model and the experimental conditions will significantly hinder the reconstruction accuracy. Therefore, the reference measurement is commonly used to calibrate the measured data before the reconstruction. However, it is complicated to customize corresponding reference phantoms based on the breast shape and background optical parameters of different subjects in clinical trials. Furthermore, although high-density (HD) DOT configuration has been proven to improve imaging quality, a large number of source-detector (SD) pairs also increase the difficulty of multi-channel correction. To enhance the applicability of the breast DOT, a data self-calibration method based on an HD parallel-plate DOT system is proposed in this paper to replace the conventional relative measurement on a reference phantom. The reference predicted data can be constructed directly from the measurement data with the support of the HD-DOT system, which has nearly a hundred sets of measurements at each SD distance. The proposed scheme has been validated by Monte Carlo (MC) simulation, breast-size phantom experiments, and clinical trials, exhibiting the feasibility in ensuring the quality of the DOT reconstruction while effectively reducing the complexity associated with relative measurements on reference phantoms.
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Reviewed by: Jinchao Feng, Beijing University of Technology, China; Junwei Shi, University of Miami, United States; Mengyu Jia, Tianjin University, China
This article was submitted to Cancer Imaging and Image-directed Interventions, a section of the journal Frontiers in Oncology
These authors have contributed equally to this work and share first authorship
Edited by: Guanglei Zhang, Beihang University, China
ISSN:2234-943X
2234-943X
DOI:10.3389/fonc.2021.786289