메뉴 건너뛰기




Volumn , Issue , 2008, Pages

An efficient framework for brain tumor segmentation in magnetic resonance images

Author keywords

Brain tumor segmentation; Expectation maximization algorithm; MRI; Region competition based level set

Indexed keywords

COMPETITION; IMAGE SEGMENTATION; IMAGING SYSTEMS; MAGNETIC RESONANCE; MAGNETIC RESONANCE IMAGING; MAXIMUM PRINCIPLE; THREE DIMENSIONAL;

EID: 63149133858     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IPTA.2008.4743791     Document Type: Conference Paper
Times cited : (4)

References (24)
  • 4
    • 63149101282 scopus 로고    scopus 로고
    • N, Moon and al. Automatic Brain and Tumor Segmentation MICCAI, 372-379, 2002.
    • N, Moon and al. Automatic Brain and Tumor Segmentation MICCAI, 372-379, 2002.
  • 5
    • 6344221605 scopus 로고    scopus 로고
    • Atlas-based Segmentation of Pathological MR Brain Using a Model of Lesion Growth
    • M.B. Cuadra and al. Atlas-based Segmentation of Pathological MR Brain Using a Model of Lesion Growth. IEEE Trans, Medical Imaging, 23:1301-1314, 2004.
    • (2004) IEEE Trans, Medical Imaging , vol.23 , pp. 1301-1314
    • Cuadra, M.B.1    and al2
  • 6
    • 4444333897 scopus 로고    scopus 로고
    • A brain tumor segmentation framework. based on outlier detection
    • M. Prastawa and al, A brain tumor segmentation framework. based on outlier detection. MedLA, 8:275-283, 2004.
    • (2004) MedLA , vol.8 , pp. 275-283
    • Prastawa, M.1    and al2
  • 7
    • 33751563521 scopus 로고    scopus 로고
    • Level set evolution with region competition: Automatic. 3-D segmentation of brain tumors, 16th Int, Conf on Pattern Recognition
    • S. Ho, E. Bullitt and G. Gerig. Level set evolution with region competition: Automatic. 3-D segmentation of brain tumors, 16th Int, Conf on Pattern Recognition ICPR, 20(8):532-535, 2002.
    • (2002) ICPR , vol.20 , Issue.8 , pp. 532-535
    • Ho, S.1    Bullitt, E.2    Gerig, G.3
  • 8
    • 0035413307 scopus 로고    scopus 로고
    • Automated Segment ation of Multiple Sclerosis Lesions by Model Outlier Detection
    • K.V. Leemput and al. Automated Segment ation of Multiple Sclerosis Lesions by Model Outlier Detection. IEEE Trans Med Imaging, 20(8): 2001.
    • (2001) IEEE Trans Med Imaging , vol.20 , Issue.8
    • Leemput, K.V.1    and al2
  • 12
    • 0025465145 scopus 로고
    • Scale-space and edge detection using anisotropic diffusion
    • P. Perona and J. Malik, Scale-space and edge detection using anisotropic diffusion. IEEE Trans, Med. Imaging, 12:629-639, 1990.
    • (1990) IEEE Trans, Med. Imaging , vol.12 , pp. 629-639
    • Perona, P.1    Malik, J.2
  • 13
    • 0036828879 scopus 로고    scopus 로고
    • Robust Automated Brain Extraction
    • S.M. Smith Robust Automated Brain Extraction Human Brain Mapping, 17:143-155, 2002.
    • (2002) Human Brain Mapping , vol.17 , pp. 143-155
    • Smith, S.M.1
  • 14
    • 84861349678 scopus 로고    scopus 로고
    • Reducing Aliasing Artifacts in Iso-Surfaces of Binary Volumes
    • R. Whitaker. Reducing Aliasing Artifacts in Iso-Surfaces of Binary Volumes. IEEE Volume Visual, and Graph, Symposium, 21:23-32, 2000.
    • (2000) IEEE Volume Visual, and Graph, Symposium , vol.21 , pp. 23-32
    • Whitaker, R.1
  • 15
    • 84971372881 scopus 로고
    • Marching cubes: A high-resolution 3-D surface construction algorithm
    • W.E. Lorensen and H.E. Chine. Marching cubes: A high-resolution 3-D surface construction algorithm. ACM Comput. Graph, 21:161-170, 1987.
    • (1987) ACM Comput. Graph , vol.21 , pp. 161-170
    • Lorensen, W.E.1    Chine, H.E.2
  • 17
    • 63149168686 scopus 로고
    • Image Analysis and Mathematical Morphology
    • J.P. Sem, Image Analysis and Mathematical Morphology, Academic Press Inc, 1982.
    • (1982) Academic Press Inc
    • Sem, J.P.1
  • 18
    • 0000882344 scopus 로고    scopus 로고
    • C. B aillard and al. Cooperation between Leyel Set Techniques and 3D Registration for the Segmentation of Brain Structures. ICPR, 991-994, 2000.
    • C. B aillard and al. Cooperation between Leyel Set Techniques and 3D Registration for the Segmentation of Brain Structures. ICPR, 991-994, 2000.
  • 19
    • 0036989044 scopus 로고    scopus 로고
    • Computer Vision and Pattern Recognition Techniques for 2-D and 3-D MR Cerebral Cortical Segmentation Part I): A State-of-the-Art Review
    • J.S. Suri and S. Singh and L. Reden. Computer Vision and Pattern Recognition Techniques for 2-D and 3-D MR Cerebral Cortical Segmentation Part I): A State-of-the-Art Review, Pattern Analy and Appli, 5:46-764, 2002.
    • (2002) Pattern Analy and Appli , vol.5 , pp. 46-764
    • Suri, J.S.1    Singh, S.2    Reden, L.3
  • 20
    • 33746015928 scopus 로고    scopus 로고
    • Current Methods in the Automatic Tissue Segmentation of 3D Magnetic Resonance Brain Images
    • A.W.C. Liew and H. Yan Current Methods in the Automatic Tissue Segmentation of 3D Magnetic Resonance Brain Images. Current Medical Imaging Reviews, 2:91-103, 2006.
    • (2006) Current Medical Imaging Reviews , vol.2 , pp. 91-103
    • Liew, A.W.C.1    Yan, H.2
  • 23
    • 0034151398 scopus 로고    scopus 로고
    • Adaptive, Template Moderated, Spatially Varying Statistical Classification
    • S.K. Warfield, M. Kaus, F.A. Jolesz and R. Kikinis. Adaptive, Template Moderated, Spatially Varying Statistical Classification. Medical Image Analysis, 20(8):43-55, 2000.
    • (2000) Medical Image Analysis , vol.20 , Issue.8 , pp. 43-55
    • Warfield, S.K.1    Kaus, M.2    Jolesz, F.A.3    Kikinis, R.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.