메뉴 건너뛰기




Volumn 6516, Issue , 2007, Pages

Content-based image retrieval for pulmonary computed tomography nodule images

Author keywords

Co occurrence matrix; Content based image retrieval; Gabor filter; Markov random field; Texture feature

Indexed keywords

BIOLOGICAL ORGANS; COMPUTERIZED TOMOGRAPHY; DATABASE SYSTEMS; IMAGE RECONSTRUCTION; IMAGE RESOLUTION; TEXTURES;

EID: 35148868698     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.710297     Document Type: Conference Paper
Times cited : (38)

References (34)
  • 1
    • 17644427902 scopus 로고    scopus 로고
    • American Cancer Society
    • Cancer Facts and Figures, American Cancer Society, 2006.
    • (2006) Cancer Facts and Figures
  • 4
    • 0026900840 scopus 로고
    • Performance evaluation for four classes of textural features
    • P. P. Ohanian and R. C. Dubest, "Performance evaluation for four classes of textural features," Pattern Recognition 25(8), p. 819, 1992.
    • (1992) Pattern Recognition , vol.25 , Issue.8 , pp. 819
    • Ohanian, P.P.1    Dubest, R.C.2
  • 6
    • 1242318724 scopus 로고    scopus 로고
    • A review of content-based image retrieval systems in medical applications - clinical benefits and future directions
    • February
    • H. Mller, N. Michoux, D. Bandon, and A. Geissbuhler, "A review of content-based image retrieval systems in medical applications - clinical benefits and future directions," International Journal, of Medical Informatics 73, pp. 1-23, February 2004.
    • (2004) International Journal, of Medical Informatics , vol.73 , pp. 1-23
    • Mller, H.1    Michoux, N.2    Bandon, D.3    Geissbuhler, A.4
  • 9
    • 0037600549 scopus 로고    scopus 로고
    • Automated storage and retrieval of thin-section ct images to assist diagnosis: System description and preliminary assessment
    • July
    • A. M. Aisen, L. S. Broderick, H. Winer-Muram, C. E. Brodley, A. C. Kak, C. Pavlopoulou, J. Dy, C.-R. Shyu, and A. Marchiori, "Automated storage and retrieval of thin-section ct images to assist diagnosis: System description and preliminary assessment," Radiology 228, pp. 265-270, July 2003.
    • (2003) Radiology , vol.228 , pp. 265-270
    • Aisen, A.M.1    Broderick, L.S.2    Winer-Muram, H.3    Brodley, C.E.4    Kak, A.C.5    Pavlopoulou, C.6    Dy, J.7    Shyu, C.-R.8    Marchiori, A.9
  • 11
    • 0041428219 scopus 로고    scopus 로고
    • Obstructive lung diseases: Texture classification for differentiation at ct
    • September
    • F. Chabat, G.-Z. Yang, and D. M. Hansell, "Obstructive lung diseases: Texture classification for differentiation at ct," Radiology 228, pp. 871-877, September 2003.
    • (2003) Radiology , vol.228 , pp. 871-877
    • Chabat, F.1    Yang, G.-Z.2    Hansell, D.M.3
  • 12
    • 0038287738 scopus 로고    scopus 로고
    • Pulmonary nodule detection using chest ct images
    • D.-Y. Kim, J.-H. Kim, S.-M. Noh, and J.-W. Park, "Pulmonary nodule detection using chest ct images," Acta Radiologica (44), pp. 252-257, 2003.
    • (2003) Acta Radiologica , vol.44 , pp. 252-257
    • Kim, D.-Y.1    Kim, J.-H.2    Noh, S.-M.3    Park, J.-W.4
  • 13
    • 0036182280 scopus 로고    scopus 로고
    • Usefulness of an artificial neural network for differentiating benign from malignant pulmonary nodules on high-resolution ct
    • March
    • Y. Matsuki, K. Nakamura, H. Watanabe, T. Aoki, H. Nakata, S. Katsuragawa, and K. Doi, "Usefulness of an artificial neural network for differentiating benign from malignant pulmonary nodules on high-resolution ct," American Journal of Roentgenology, pp. 657-663, March 2002.
    • (2002) American Journal of Roentgenology , pp. 657-663
    • Matsuki, Y.1    Nakamura, K.2    Watanabe, H.3    Aoki, T.4    Nakata, H.5    Katsuragawa, S.6    Doi, K.7
  • 17
    • 0007367697 scopus 로고    scopus 로고
    • Texture analysis methods - a review
    • Technical University of Lodz, Institute of Electronics, COST B11 report
    • A. Materka and M. Strzelecki, "Texture analysis methods - a review," tech. rep., Technical University of Lodz, Institute of Electronics, 1998. COST B11 report.
    • (1998) tech. rep
    • Materka, A.1    Strzelecki, M.2
  • 18
    • 35148847463 scopus 로고    scopus 로고
    • Pixel-based texture classification of tissues in computed tomography
    • April
    • R. Susomboon, D. Raicu, and J. Furst, "Pixel-based texture classification of tissues in computed tomography," in CTI Research Symposium, April 2006.
    • (2006) CTI Research Symposium
    • Susomboon, R.1    Raicu, D.2    Furst, J.3
  • 22
    • 0034333640 scopus 로고    scopus 로고
    • Designing gabor filters for optimal texture separability
    • D. A. Clausi and M. E. Jernigan, "Designing gabor filters for optimal texture separability," Pattern Recognition 33, pp. 1835-1849, 2000.
    • (2000) Pattern Recognition , vol.33 , pp. 1835-1849
    • Clausi, D.A.1    Jernigan, M.E.2
  • 24
    • 0003969922 scopus 로고    scopus 로고
    • C. Chen, L. Pau, and P. W, eds, 2nd Edition, World Scientific Publishing Company
    • C. Chen, L. Pau, and P. W. (eds.), The Handbook of Pattern Recognition and Computer Vision (2nd Edition), World Scientific Publishing Company, 1998.
    • (1998) The Handbook of Pattern Recognition and Computer Vision
  • 27
    • 0035272095 scopus 로고    scopus 로고
    • Texture segmentation using gaussian-markov random fields and neural oscillator networks
    • March
    • E. Cesmeli and D.Wang, "Texture segmentation using gaussian-markov random fields and neural oscillator networks," IEEE Transactions on Neural Networks 12, pp. 394-404, March 2001.
    • (2001) IEEE Transactions on Neural Networks , vol.12 , pp. 394-404
    • Cesmeli, E.1    Wang, D.2
  • 28
    • 0033284807 scopus 로고    scopus 로고
    • Empirical evaluation of dissimilarity measures for color and texture
    • J. Puzicha, Y. Rubner, C. Tomasi, and J. M. Buhmann, "Empirical evaluation of dissimilarity measures for color and texture," in ICCV (2), pp. 1165-1172, 1999.
    • (1999) ICCV , vol.2 , pp. 1165-1172
    • Puzicha, J.1    Rubner, Y.2    Tomasi, C.3    Buhmann, J.M.4
  • 29
    • 84878883767 scopus 로고    scopus 로고
    • National Cancer Imaging Archive
    • LIDC Lung Nodule Image Database, National Cancer Imaging Archive (https://imaging.nci.nih.gov/ncia/).
    • LIDC Lung Nodule Image Database
  • 30
    • 35148874771 scopus 로고    scopus 로고
    • SourceForge http
    • openDICOM.net, SourceForge (http://opendicom.sourceforge.net/).
    • openDICOM.net


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.