Automated Segmentation of Lung Lobes and Recognition of Pulmonary Nodules from Multi-slice Chest X-ray CT Images

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概要

• 論文の詳細を見る

• The aim of our CAD (computer-aided diagnostic) system is to discover indistinct nodules in Chest X-ray CT. We firstly get the accurate segmentation of lung lobes from multi-slice images based on an improved rolling ball algorithm using morphology. Secondly a multiple-template matching technique was used to search for the location of nodules in the lung areas, where image fusion of true nodules were used as templates. We finally focus on the elimination of blood vessels by using the 3D reconstruction of detected nodules position. Experiments show that 78% detection rate with approximately 85% false positives elimination rate.

• 社団法人電子情報通信学会の論文
• 2007-01-19

著者

• Jiang Hui-yan

  Sino-dutch Biomedical And Information Engineering School Northeastern University:computing Center No

• Zhao Yue

  Sino-dutch Biomedical And Information Engineering School Northeastern University

• Li Yue-jun

  Sino-dutch Biomedical And Information Engineering School Northeastern University

• Cheng Zhen-yu

  Sino-Dutch Biomedical and Information Engineering School, Northeastern University

• Cheng Zhen-yu

  Sino-dutch Biomedical And Information Engineering School Northeastern University

• Cheng Zhen‐yu

  Sino-dutch Biomedical And Information Engineering School Northeastern University

関連論文

• Segmentation of Pulmonary Nodules Based on Improved Dual Fast Marching Method
• Automated Segmentation of Lung Lobes and Recognition of Pulmonary Nodules from Multi-slice Chest X-ray CT Images

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