Poster + Paper
8 March 2023 Uncertainty measurement and confidence calibration for calcium detection in optical coherence images
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Conference Poster
Abstract
Optical coherence tomography (OCT) has become increasingly essential in assisting the treatment of coronary artery disease (CAD). Image-guided solutions such as Percutaneous Coronary Intervention (PCI) are extensively used during the treatment of CAD. However, unidentified calcified regions within a narrowed artery could impair the outcome of the PCI. Prior to treatments, object detection of the diseased regions is paramount to automatically procure accurate readings on calcifications within the artery. Though deep learning-based object detection methods have been explored in a variety of applications, the quality of predictions can be negatively impacted by overconfident deep learning models, which is not desirable in safety-critical scenarios. In this work, we adopt an object detection model to rapidly draw the calcified region from coronary OCT images using bounding box. We evaluate the uncertainty of predictions based on the expected calibration errors, thus assessing the certainty level of detection results. The calibrated confidence of prediction results in a confidence error of approximately 0.13, suggesting that the confidence calibration on calcification detection could provide a more trustworthy result, which indicates a great potential to assist clinical evaluation of treating the CAD during the imaging-guided procedure.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hongshan Liu, Abdul Latif Bamba, and Yu Gan "Uncertainty measurement and confidence calibration for calcium detection in optical coherence images", Proc. SPIE 12367, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXVII, 1236715 (8 March 2023); https://doi.org/10.1117/12.2652944
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KEYWORDS
Object detection

Calibration

Optical coherence tomography

Measurement uncertainty

Calcium

Deep learning

Arteries

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