Automatic skin lesion area determination of basal cell carcinoma using optical coherence tomography angiography and a skeletonization approach: Preliminary results. Issue 9 (18th June 2019)

• Record Type: Journal Article
• Authors: Meiburger, Kristen M.; Chen, Zhe; Sinz, Christoph; Hoover, Erich; Minneman, Michael; Ensher, Jason; Kittler, Harald; Leitgeb, Rainer A.; Drexler, Wolfgang; Liu, Mengyang
• Is Part Of: Journal of biophotonics. Volume 12:Issue 9(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-06-18
• Subjects: basal cell carcinoma -- computer‐aided detection -- optical coherence tomography angiography -- quantification -- skeletonization; Photonics -- Periodicals; Optical materials -- Periodicals; Optics -- Periodicals; Medical instruments and apparatus -- Periodicals; 621.3605
• DOI: 10.1002/jbio.201900131
• Languages: English
• ISSNs: 1864-063X

Abstract

Abstract: Cutaneous blood flow plays a key role in numerous physiological and pathological processes and has significant potential to be used as a biomarker to diagnose skin diseases such as basal cell carcinoma (BCC). The determination of the lesion area and vascular parameters within it, such as vessel density, is essential for diagnosis, surgical treatment and follow‐up procedures. Here, an automatic skin lesion area determination algorithm based on optical coherence tomography angiography (OCTA) images is presented for the first time. The blood vessels are segmented within the OCTA images and then skeletonized. Subsequently, the skeleton is searched over the volume and numerous quantitative vascular parameters are calculated. The vascular density is then used to segment the lesion area. The algorithm is tested on both nodular and superficial BCC, and comparing with dermatological and histological results, the proposed method provides an accurate, non‐invasive, quantitative and automatic tool for BCC lesion area determination. Abstract : Cutaneous blood flow is fundamental in various physiological and pathological processes and could be used as a biomarker to diagnose skin diseases, such as basal cell carcinoma (BCC). The determination of the lesion area and quantitative vascular parameters is essential for diagnosis, surgical treatment and follow‐up procedures. Here, a completely automated solution for BCC lesion area determination is presented, and quantitative vascular parameters are calculated within and outside the lesion.