Cargando…
Automatic skin lesion area determination of basal cell carcinoma using optical coherence tomography angiography and a skeletonization approach: Preliminary results
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 dens...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
WILEY‐VCH Verlag GmbH & Co. KGaA
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7065618/ https://www.ncbi.nlm.nih.gov/pubmed/31100191 http://dx.doi.org/10.1002/jbio.201900131 |
_version_ | 1783505091417866240 |
---|---|
author | Meiburger, Kristen M. Chen, Zhe Sinz, Christoph Hoover, Erich Minneman, Michael Ensher, Jason Kittler, Harald Leitgeb, Rainer A. Drexler, Wolfgang Liu, Mengyang |
author_facet | Meiburger, Kristen M. Chen, Zhe Sinz, Christoph Hoover, Erich Minneman, Michael Ensher, Jason Kittler, Harald Leitgeb, Rainer A. Drexler, Wolfgang Liu, Mengyang |
author_sort | Meiburger, Kristen M. |
collection | PubMed |
description | 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. [Image: see text] |
format | Online Article Text |
id | pubmed-7065618 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | WILEY‐VCH Verlag GmbH & Co. KGaA |
record_format | MEDLINE/PubMed |
spelling | pubmed-70656182020-03-16 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 J Biophotonics Full Articles 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. [Image: see text] WILEY‐VCH Verlag GmbH & Co. KGaA 2019-06-18 2019-09 /pmc/articles/PMC7065618/ /pubmed/31100191 http://dx.doi.org/10.1002/jbio.201900131 Text en © 2019 The Authors. Journal of Biophotonics published by WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Full Articles Meiburger, Kristen M. Chen, Zhe Sinz, Christoph Hoover, Erich Minneman, Michael Ensher, Jason Kittler, Harald Leitgeb, Rainer A. Drexler, Wolfgang Liu, Mengyang Automatic skin lesion area determination of basal cell carcinoma using optical coherence tomography angiography and a skeletonization approach: Preliminary results |
title | Automatic skin lesion area determination of basal cell carcinoma using optical coherence tomography angiography and a skeletonization approach: Preliminary results |
title_full | Automatic skin lesion area determination of basal cell carcinoma using optical coherence tomography angiography and a skeletonization approach: Preliminary results |
title_fullStr | Automatic skin lesion area determination of basal cell carcinoma using optical coherence tomography angiography and a skeletonization approach: Preliminary results |
title_full_unstemmed | Automatic skin lesion area determination of basal cell carcinoma using optical coherence tomography angiography and a skeletonization approach: Preliminary results |
title_short | Automatic skin lesion area determination of basal cell carcinoma using optical coherence tomography angiography and a skeletonization approach: Preliminary results |
title_sort | automatic skin lesion area determination of basal cell carcinoma using optical coherence tomography angiography and a skeletonization approach: preliminary results |
topic | Full Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7065618/ https://www.ncbi.nlm.nih.gov/pubmed/31100191 http://dx.doi.org/10.1002/jbio.201900131 |
work_keys_str_mv | AT meiburgerkristenm automaticskinlesionareadeterminationofbasalcellcarcinomausingopticalcoherencetomographyangiographyandaskeletonizationapproachpreliminaryresults AT chenzhe automaticskinlesionareadeterminationofbasalcellcarcinomausingopticalcoherencetomographyangiographyandaskeletonizationapproachpreliminaryresults AT sinzchristoph automaticskinlesionareadeterminationofbasalcellcarcinomausingopticalcoherencetomographyangiographyandaskeletonizationapproachpreliminaryresults AT hoovererich automaticskinlesionareadeterminationofbasalcellcarcinomausingopticalcoherencetomographyangiographyandaskeletonizationapproachpreliminaryresults AT minnemanmichael automaticskinlesionareadeterminationofbasalcellcarcinomausingopticalcoherencetomographyangiographyandaskeletonizationapproachpreliminaryresults AT ensherjason automaticskinlesionareadeterminationofbasalcellcarcinomausingopticalcoherencetomographyangiographyandaskeletonizationapproachpreliminaryresults AT kittlerharald automaticskinlesionareadeterminationofbasalcellcarcinomausingopticalcoherencetomographyangiographyandaskeletonizationapproachpreliminaryresults AT leitgebrainera automaticskinlesionareadeterminationofbasalcellcarcinomausingopticalcoherencetomographyangiographyandaskeletonizationapproachpreliminaryresults AT drexlerwolfgang automaticskinlesionareadeterminationofbasalcellcarcinomausingopticalcoherencetomographyangiographyandaskeletonizationapproachpreliminaryresults AT liumengyang automaticskinlesionareadeterminationofbasalcellcarcinomausingopticalcoherencetomographyangiographyandaskeletonizationapproachpreliminaryresults |