Download
s13104-021-05650-4.pdf 780,18KB
WeightNameValue
1000 Titel
  • Computer-aided clinical image analysis for non-invasive assessment of tumor thickness in cutaneous melanoma
1000 Autor/in
  1. Papadakis, Marios |
  2. Paschos, Alexandros |
  3. Manios, Andreas |
  4. Lehmann, Percy |
  5. Manios, Georgios |
  6. Zirngibl, Hubert |
1000 Erscheinungsjahr 2021
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-06-14
1000 Erschienen in
1000 Quellenangabe
  • 14(1):232
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s13104-021-05650-4 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201878/ |
1000 Publikationsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Objective!#!Computerized clinical image analysis is shown to improve diagnostic accuracy for cutaneous melanoma but its effectiveness in preoperative assessment of melanoma thickness has not been studied. The aim of this study, is to explore how melanoma thickness correlates with computer-assisted objectively obtained color and geometric variables. All patients diagnosed with cutaneous melanoma with available clinical images prior to tumor excision were included in the study. All images underwent digital processing with an automated non-commercial software. The software provided measurements for geometrical variables, i.e., overall lesion surface, maximum diameter, perimeter, circularity, eccentricity, mean radius, as well as for color variables, i.e., range, standard deviation, coefficient of variation and skewness in the red, green, and blue color space.!##!Results!#!One hundred fifty-six lesions were included in the final analysis. The mean tumor thickness was 1.84 mm (range 0.2-25). Melanoma thickness was strongly correlated with overall surface area, maximum diameter, perimeter and mean lesion radius. Thickness was moderately correlated with eccentricity, green color and blue color. We conclude that geometrical and color parameters, as objectively extracted by computer-aided clinical image processing, may correlate with tumor thickness in patients with cutaneous melanoma. However, these correlations are not strong enough to reliably predict tumor thickness.
1000 Sacherschließung
lokal Melanoma/diagnostic imaging [MeSH]
lokal Sensitivity and Specificity [MeSH]
lokal Humans [MeSH]
lokal Image Processing, Computer-Assisted [MeSH]
lokal Software [MeSH]
lokal Biomedicine, general
lokal Skin Neoplasms/diagnostic imaging [MeSH]
lokal Life Sciences, general
lokal Medicine/Public Health, general
lokal Research Note
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0002-9020-874X|https://frl.publisso.de/adhoc/uri/UGFzY2hvcywgQWxleGFuZHJvcw==|https://frl.publisso.de/adhoc/uri/TWFuaW9zLCBBbmRyZWFz|https://frl.publisso.de/adhoc/uri/TGVobWFubiwgUGVyY3k=|https://frl.publisso.de/adhoc/uri/TWFuaW9zLCBHZW9yZ2lvcw==|https://frl.publisso.de/adhoc/uri/WmlybmdpYmwsIEh1YmVydA==
1000 Hinweis
  • DeepGreen-ID: 9033a31885e1474795a39e2c96000f76 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
1000 Label
1000 Dateien
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6463957.rdf
1000 Erstellt am 2023-11-15T23:05:22.948+0100
1000 Erstellt von 322
1000 beschreibt frl:6463957
1000 Zuletzt bearbeitet Thu Nov 30 22:41:53 CET 2023
1000 Objekt bearb. Thu Nov 30 22:41:53 CET 2023
1000 Vgl. frl:6463957
1000 Oai Id
  1. oai:frl.publisso.de:frl:6463957 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

View source