3d Lung Vessel Segmentation In Computed Tomography Angiography Images
Öz
In this paper, a novel lung vessel segmentation method is introduced. In this method, some Reference Points (RPs) were determined by making use of the properties of unchangeable anatomical structure. Due to these RPs, truncus, left-right pulmonary artery, lobar segment vessels have been segmented and subsegment vessels have been detected by looking at the differences of intensities in lung region. If there is pulmonary emboli (PE), heart disease, or abnormal tissues, vessel structure doesn't regularly continue and decreases the sensitivity of segmentation. Using RPs, vessel structure becomes more definite and sensitivity of the segmentation increases. CTA images belonging 30 patients including different disease are examined and 95% of sensitivity is obtained. The performance of the method for lung vessel segmentation is found to be quite well for radiologists and it gives enough results to the surgeries medically.
Anahtar Kelimeler
Kaynakça
- J. M. Remy, L. I. Tillie, D. Szapiro, “CT angiography of pulmonary embolism in patients with underlying respiratory disease: impact of multislice CT on image quality and negative predictive value”. Eur Radiol 12:1971–1978, 2002.
- J. E. Dalen, “Pulmonary embolism: What have we learned since Virchow”, Chest,122: 1440-1446, 2002.
- H. P. Chan, L. Hadjiiski, C. Zhou, et al., “Computer- aided diagnosis of lung cancer and pulmonary embolism in computed tomography – a review”, Acad Radiol 15:535–555, 2008.
- Y. Masutani, H. Macmahon, and K. Doi, “Computer-assisted embolism”, In SPIE Medical Imaging 2000, San Diego, USA, February 2000. of pulmonary
- J. N. Kaftan, A. P. Kiraly, A. Bakai, M. Das, C. L. Novak, and T. Aach, “Fuzzy Pulmonary Vessel Segmentation in Contrast Enhanced CT data”, Medical Imaging, February 2008.
- S. Ozekes, O. Osman, “Computerized Lung Nodule Detection Using 3D Feature Extraction and Learning Based Algorithms”, Journal of Medical Systems, Volume: 34 Issue: 2 Pages: 185-194, APR 2010.
- S. Ozekes, O. Osman, O. N. Ucan, “Nodule Detection in the Lung Region, which is Segmented with Genetic Cellular Neural Networks, Using 3D Template Matching with Fuzzy Rule Based Thresholding”, Korean Journal of Radiology, Vol.9, No.1, pp.1-9, 2008.
- R. Uppaluri, E. Hoffman, M. Sonka, P. Hartley, “Hunninghake, and G. Mclennan, “Computer recognition of regional lung disease patterns”, Am. J. Respir. Crit. Care Med. 160, 648–654, 1999.
Ayrıntılar
Birincil Dil
İngilizce
Konular
-
Bölüm
-
Yazarlar
Yayımlanma Tarihi
2 Eylül 2013
Gönderilme Tarihi
2 Eylül 2013
Kabul Tarihi
-
Yayımlandığı Sayı
Yıl 2012 Cilt: 12 Sayı: 1