Extraction of Ground Glass Opacities in Lung CT Images Using Subtraction

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  • TACHIBANA Rie
    Information Science and Technology Department, National Institute of Technology, Oshima College
  • HIRANO Yasushi
    Graduate School of Medicine, Yamaguchi University
  • XU Rui
    Ritsumeikan University
  • KIDO Shoji
    Graduate School of Medicine, Yamaguchi University
  • KIM Hyoungseop
    Graduate School of Engineering, Kyushu Institute of Technology

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  • 差分処理を用いた胸部CT画像上におけるすりガラス陰影の領域抽出

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Abstract

Pulmonary nodules with ground glass opacity (GGO) in lung CT images are difficult to differential diagnosis, and follow-up are often performed. In cases of follow-up, the present CT images are compared with past CT images, and it is necessary to evaluate the changes quantitatively. So, we have developed a volumetric segmentation algorithm of pulmonary nodules with GGO on CT images. Nodules with GGO, especially pure-GGO, are difficult to define a threshold value. Therefore, our algorithm does not define a threshold value. In our algorithm, the first step is to emphasize CT images using the sigmoid function. Next, the nodule is roughly segmented with background subtraction. Finally the nodule without vessels is decided by morphological operation, etc. For evaluation of our algorithm, we selected nodules with GGO from the dataset provided by LIDC (The Lung Image Database Consortium). In this paper, we illustrate some experimental result w hich applied our algorithm.

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