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Image‐processing chain for a three‐dimensional reconstruction of basal cell carcinomas * †
Author(s) -
Scheibe Patrick,
Braumann UlfDietrich,
Kuska JensPeer,
Löffler Markus,
Simon Jan C.,
Paasch Uwe,
Wetzig Tino
Publication year - 2010
Publication title -
experimental dermatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 96
eISSN - 1600-0625
pISSN - 0906-6705
DOI - 10.1111/j.1600-0625.2010.01100.x
Subject(s) - basal cell carcinoma , artificial intelligence , segmentation , computer science , image processing , maxima and minima , basal cell , computer vision , process (computing) , skin cancer , basal (medicine) , pattern recognition (psychology) , image (mathematics) , pathology , computational biology , cancer , medicine , biology , mathematics , insulin , operating system , mathematical analysis
Please cite this paper as : Image‐processing chain for a three‐dimensional reconstruction of basal cell carcinomas. Experimental Dermatology 2010; 19: 689–691. Abstract: Basal cell carcinoma (BCC) is the most common malignant skin cancer. For a deeper insight into the specific growth patterns of the tumorous tissue in BCC, we have focused on the development of a novel automated image‐processing chain for 3D reconstruction of BCC using histopathological serial sections. For fully automatic delineation of the tumor within the tissue, we apply a fuzzy c‐means segmentation method. We used a novel multi‐grid form of the non‐linear registration introduced by Braumann and Kuska in 2005 effectively suppressing registration runs into local minima (possibly caused by diffuse nature of the tumor). Our method was successfully applied in a proof‐of‐principle study for automated reconstruction.