CNNを用いたX線投影画像のノイズ除去に基づいたCTスキャンニングの品質向上

DOI

書誌事項

タイトル別名
  • Quality Improvement of CT Scanning Using CNN-based Denoising of X-ray Transmission Images

説明

<p>High precision 3D models can be used for various purpose like reverse engineering, flaw detection etc. However, to obatin such models, a large amount of projection images with low noise level are required and to get images with low noise level, the scanning time is very long. The purpose of my research is to denoise noisy CT images obtained from fast scanning, thus making them be eligible to be used for high precision reconstuction, reducing the total processing time. I applied deep learning approach to solve this problem, which I used a CNN with deep structure and two unique techniques: residual learning and batch normalization. The noise level of images are significantly reduced, and gained a more satisfying result than traditional methods.The total processing time is also reduced significantly.</p>

収録刊行物

キーワード

詳細情報 詳細情報について

  • CRID
    1390004222624863232
  • NII論文ID
    130007896528
  • DOI
    10.11522/pscjspe.2020s.0_202
  • 本文言語コード
    en
  • データソース種別
    • JaLC
    • CiNii Articles
  • 抄録ライセンスフラグ
    使用不可

問題の指摘

ページトップへ