メラノーマ特徴を付与した大量擬似画像を用いた説明可能な自動診断システム構築の試み

DOI HANDLE

書誌事項

タイトル別名
  • EXPLAINABLE DIAGNOSIS SYSTEM USING BULK PRODUCTION OF PSEUDO-IMAGES WITH MELANOMA FEATURES

この論文をさがす

説明

Although highly accurate automated diagnostic techniques for melanoma have been reported, the realization of a system capable of providing diagnostic evidence based on medical indices remains an open issue because of difficulties in obtaining reliable training data. In this paper, we propose bulk production augmentation (BPA) to generate high-quality, diverse pseudo-skin tumor images with the desired structural malignant features for additional training images from a limited number of labeled images. The proposed BPA acts as an effective data augmentation in constructing the feature detector for the atypical pigment network (APN), which is a key structure in melanoma diagnosis. Experiments show that training with images generated by our BPA largely boosts the APN detection performance by 20.0 points in the area under the receiver operating characteristic curve, which is 11.5 to 13.7 points higher than that of conventional CycleGAN-based augmentations in AUC.

収録刊行物

キーワード

詳細情報 詳細情報について

  • CRID
    1390009225531800576
  • NII論文ID
    120007119612
  • NII書誌ID
    AA12677220
  • DOI
    10.15002/00023963
  • HANDLE
    10114/00023963
  • ISSN
    21879923
  • 本文言語コード
    ja
  • データソース種別
    • JaLC
    • IRDB
    • CiNii Articles
  • 抄録ライセンスフラグ
    使用可

問題の指摘

ページトップへ