Algorithm of pulmonary emphysema extraction using thoracic 3-D CT images

Shinsuke Saita; Mitsuru Kubo; Yoshiki Kawata; Noboru Niki; Yasutaka Nakano; Hironobu Ohmatsu; Keigo Tominaga; Kenji Eguchi; Noriyuki Moriyama

doi:10.1117/12.769968

17 March 2008 Algorithm of pulmonary emphysema extraction using thoracic 3-D CT images

Shinsuke Saita, Mitsuru Kubo, Yoshiki Kawata, Noboru Niki, Yasutaka Nakano, Hironobu Ohmatsu, Keigo Tominaga, Kenji Eguchi, Noriyuki Moriyama

Author Affiliations +

Proceedings Volume 6915, Medical Imaging 2008: Computer-Aided Diagnosis; 69152L (2008) https://doi.org/10.1117/12.769968
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

Emphysema patients have the tendency to increase due to aging and smoking. Emphysematous disease destroys alveolus and to repair is impossible, thus early detection is essential. CT value of lung tissue decreases due to the destruction of lung structure. This CT value becomes lower than the normal lung- low density absorption region or referred to as Low Attenuation Area (LAA). So far, the conventional way of extracting LAA by simple thresholding has been proposed. However, the CT value of CT image fluctuates due to the measurement conditions, with various bias components such as inspiration, expiration and congestion. It is therefore necessary to consider these bias components in the extraction of LAA. We removed these bias components and we proposed LAA extraction algorithm. This algorithm has been applied to the phantom image. Then, by using the low dose CT(normal: 30 cases, obstructive lung disease: 26 cases), we extracted early stage LAA and quantitatively analyzed lung lobes using lung structure.

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Shinsuke Saita, Mitsuru Kubo, Yoshiki Kawata, Noboru Niki, Yasutaka Nakano, Hironobu Ohmatsu, Keigo Tominaga, Kenji Eguchi, and Noriyuki Moriyama "Algorithm of pulmonary emphysema extraction using thoracic 3-D CT images", Proc. SPIE 6915, Medical Imaging 2008: Computer-Aided Diagnosis, 69152L (17 March 2008); https://doi.org/10.1117/12.769968

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