Region extraction method for skin grafts via image analysis

Daijiro Wada, Soichiro Kato, Yoshihiro Yamaguchi, Toshiyuki Tanaka

研究成果: Article査読

抄録

Dermal grafts are used for patients with severe burn injuries whose natural healing abilities are limited or exhausted. This paper proposes a method to segment burnt and grafted areas from images with meshed grafts. First, RGB colour input images are converted to images in the L*a*b* colour space. The transformed images are then segmented with the simple linear iterative clustering superpixel algorithm. Subsequently, the burnt and grafted areas are classified with a support vector machine, and the output area size is modified for all burnt areas. The segmentation results are compared with the areas identified by two dermatologists based on the concordance rate (CR), positive predictive value (PPV), sensitivity, and F-measure values. The proposed segmentation method yielded CRs equal to 84.3 % and 85.9 %, PPVs equal to 87.2 % and 87.9 %, sensitivities equal to 84.7 % and 86.4 %, and F-measure values equal to 85.8 % and 87.0 %. This study developed a segmentation method for classifying burnt and grafted areas from images with meshed grafts. The segmented areas obtained were significantly consistent with those identified by the two dermatologists.

本文言語English
ページ(範囲)22-37
ページ数16
ジャーナルComputer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization
10
1
DOI
出版ステータスPublished - 2022

ASJC Scopus subject areas

  • 計算力学
  • 生体医工学
  • 放射線学、核医学およびイメージング
  • コンピュータ サイエンスの応用

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