Development of a method for automated liver region extraction from contrasted 3D abdominal X-ray CT images
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- Hayashi Yuichiro
- Graduate School of Engineering, Nagoya University
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- Deguchi Daisuke
- Graduate School of Information Science, Nagoya University
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- Mori Kensaku
- Graduate School of Information Science, Nagoya University
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- Mekada Yoshito
- School of Life System Science and Technology, Chukyo University
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- Suenaga Yasuhito
- Graduate School of Information Science, Nagoya University
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- Toriwaki Junichiro
- School of Life System Science and Technology, Chukyo University
Bibliographic Information
- Other Title
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- 造影3次元腹部X線CT像からの肝臓領域自動抽出手法の開発
Abstract
In this paper, we present a method for automated extraction of the liver region from contrasted 3D abdominal CT images. Since the medical doctor diagnoses the liver using multi contrasted phase CT images, it is necessary for computer aided diagnosis system which extracts the liver region from each contrasted phase image. We propose an automated extraction method of liver regions from both the early and late arterial phase CT images. In the case of the late arterial phase, we estimate the threshold value for the liver region extraction by analyzing the CT value histogram. Then, false positive regions are removed by employing a figure decomposition and composition method based on an Euclidean distance feature. Finally, we modify the contour of the liver region. In the case of the early arterial phase, we map the liver region extracted from the late arterial phase onto the early arterial phase CT image and modify its contour. We applied the proposed method to contrasted abdominal CT images. The experimental results suggested the proposed method could extract the liver region from both phases satisfactorily.
Journal
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- Journal of Computer Aided Diagnosis of Medical Images
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Journal of Computer Aided Diagnosis of Medical Images 8 (1_3), 18-30, 2004
The Japanese Society of Medical Imaging Technology
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Keywords
Details 詳細情報について
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- CRID
- 1390001205210294784
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- NII Article ID
- 80020807679
- 130004939082
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- ISSN
- 13479245
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- Text Lang
- ja
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- Data Source
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- JaLC
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed