Abdelrehim, T.; Salah, M.; Fok, A.; Conrad, H.J.; Chew, H.P. Auto-Segmentation and Quantification of Non-Cavitated Enamel Caries Imaged with Swept-Source Optical Coherence Tomography. Diagnostics2023, 13, 3586.
Abdelrehim, T.; Salah, M.; Fok, A.; Conrad, H.J.; Chew, H.P. Auto-Segmentation and Quantification of Non-Cavitated Enamel Caries Imaged with Swept-Source Optical Coherence Tomography. Diagnostics 2023, 13, 3586.
Abdelrehim, T.; Salah, M.; Fok, A.; Conrad, H.J.; Chew, H.P. Auto-Segmentation and Quantification of Non-Cavitated Enamel Caries Imaged with Swept-Source Optical Coherence Tomography. Diagnostics2023, 13, 3586.
Abdelrehim, T.; Salah, M.; Fok, A.; Conrad, H.J.; Chew, H.P. Auto-Segmentation and Quantification of Non-Cavitated Enamel Caries Imaged with Swept-Source Optical Coherence Tomography. Diagnostics 2023, 13, 3586.
Abstract
(1) Background: OCT imaging has been used to assess enamel demineralization in dental research but is not yet developed enough to qualify as a diagnostic technique in clinics. The current capabilities of most commercial acquisition software allow for visual and qualitative assessment. There is a need for a fast and verified batch-processing algorithm for segmenting and analyzing the de-mineralized enamel. This study suggests a GUI MATLAB algorithm for processing and quantitative analysis of the demineralized enamel. (2) Methods: A group of artificially demineralized human enamels was in vitro scanned under the OCT, and ROI frames were extracted. By using a selected intensity threshold colormap, inter- (Ie) and intra- (Ia) prismatic demineralization can be segmented. A set of quantitative measurements for average demineralized depth, average line profile, and integrated reflectivity can be obtained for an accurate assessment. Real and simulated OCT frames were used for algorithm verification. (3) Results: A strong correlation between automated and known Excel measurements for the average demineralization depth was found (R² > 0.97). (4) Conclusions: OCT image segmentation and quantification of the enamel demoralization zones are possible. The algorithm can assess the future development of a real-time assessment of dental diagnostics using an oral probe OCT.
Copyright:
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