Variability in human and automatic segmentation of melanocytic lesions

In a double blind evaluation of 60 digital dermatoscopic images by 4 "junior", 4 "senior" and 4 "expert" dermatologists (dermatoscopy training respectively less than 1 year, between 1 and 5 years, and more than 5 years), a significant inter-operator variability was observed in melanocytic lesion border identification (with a disagreement of the order of 10 - 20% of the area of the lesions). Expert dermatologists showed greater agreement among themselves than with senior and junior dermatologists, and a slight tendency towards "tighter" segmentations. The human inter-operator variability was then used to evaluate the segmentation accuracy of 4 algorithms, representative of the 3 fundamental state-of-the-art automated segmentation techniques and of a fourth, novel, technique. Our evaluation methodology addresses a number of crucial difficulties encountered in previous studies and may be of independent interest. 3 of the 4 algorithms showed considerably less agreement with expert dermatologists than even senior and junior dermatologists did (with a disagreement of the order of 30% of the area of the lesions); the remaining algorithm, however, showed agreement with expert dermatologists comparable to that of other expert dermatologists.

Medienart:

E-Artikel

Erscheinungsjahr:

2009

Erschienen:

2009

Enthalten in:

Zur Gesamtaufnahme - volume:2009

Enthalten in:

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference - 2009(2009) vom: 15., Seite 5789-92

Sprache:

Englisch

Beteiligte Personen:

Silletti, A [VerfasserIn]
Peserico, E [VerfasserIn]
Mantovan, A [VerfasserIn]
Zattra, E [VerfasserIn]
Peserico, A [VerfasserIn]
Belloni Fortina, A [VerfasserIn]

Links:

Volltext

Themen:

Evaluation Study
Journal Article

Anmerkungen:

Date Completed 02.04.2010

Date Revised 28.09.2020

published: Print

Citation Status MEDLINE

doi:

10.1109/IEMBS.2009.5332543

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM193299224