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Automatic skin lesion area determination of basal cell carcinoma using optical coherence tomography angiography and a skeletonization approach: Preliminary results.
Meiburger, Kristen M; Chen, Zhe; Sinz, Christoph; Hoover, Erich; Minneman, Michael; Ensher, Jason; Kittler, Harald; Leitgeb, Rainer A; Drexler, Wolfgang; Liu, Mengyang.
Afiliação
  • Meiburger KM; Biolab, Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy.
  • Chen Z; Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
  • Sinz C; Department of Dermatology, Medical University of Vienna, Vienna, Austria.
  • Hoover E; Insight Photonic Solutions, Inc., Lafayette, CO.
  • Minneman M; Insight Photonic Solutions, Inc., Lafayette, CO.
  • Ensher J; Insight Photonic Solutions, Inc., Lafayette, CO.
  • Kittler H; Department of Dermatology, Medical University of Vienna, Vienna, Austria.
  • Leitgeb RA; Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
  • Drexler W; Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
  • Liu M; Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
J Biophotonics ; 12(9): e201900131, 2019 09.
Article em En | MEDLINE | ID: mdl-31100191
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Cutâneas / Carcinoma Basocelular / Angiografia / Tomografia de Coerência Óptica Tipo de estudo: Diagnostic_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: J Biophotonics Assunto da revista: BIOFISICA Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Itália País de publicação: ALEMANHA / ALEMANIA / DE / DEUSTCHLAND / GERMANY

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Cutâneas / Carcinoma Basocelular / Angiografia / Tomografia de Coerência Óptica Tipo de estudo: Diagnostic_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: J Biophotonics Assunto da revista: BIOFISICA Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Itália País de publicação: ALEMANHA / ALEMANIA / DE / DEUSTCHLAND / GERMANY