Focal Cortical Dysplasia (FCD) lesion analysis with complex diffusion approach

被引:11
作者
Rajan, Jeny [1 ]
Kannan, K. [1 ]
Kesavadas, C. [2 ]
Thomas, Bejoy [2 ]
机构
[1] NeST, Med Imaging Res Grp, Trivandrum 695581, Kerala, India
[2] SCTIMST, Dept Imaging Sci & Intervent Radiol, Trivandrum, Kerala, India
关键词
Complex diffusion; Cortical thickening; Epilepsy; Focal cortical dysplasia; MRI; Thickness map; AUTOMATIC SEGMENTATION; COMPUTATIONAL MODELS; MRI CHARACTERISTICS; THICKNESS; CORTEX; MATTER; BRAIN; SKULL;
D O I
10.1016/j.compmedimag.2009.05.004
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Identification of Focal Cortical Dysplasia (FCD) can be difficult due to the subtle MRI changes. Though sequences like FLAIR (fluid attenuated inversion recovery) can detect a large majority of these lesions, there are smaller lesions without signal changes that can easily go unnoticed by the naked eye. The aim of this study is to improve the visibility of focal cortical dysplasia lesions in the T1 weighted brain MRI images. In the proposed method, we used a complex diffusion based approach for calculating the FCD affected areas. Based on the diffused image and thickness map, a complex map is created. From this complex map; FCD areas can be easily identified. MRI brains of 48 subjects selected by neuroradiologists were given to computer scientists who developed the complex map for identifying the cortical dysplasia. The scientists were blinded to the MRI interpretation result of the neuroradiologist. The FCD could be identified in all the patients in whom surgery was done, however three patients had false positive lesions. More lesions were identified in patients in whom surgery was not performed and lesions were seen in few of the controls. These were considered as false positive. This computer aided detection technique using complex diffusion approach can help detect focal cortical dysplasia in patients with epilepsy. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:553 / 558
页数:6
相关论文
共 29 条
  • [1] Automated detection of focal cortical dysplasia lesions using computational models of their MRI characteristics and texture analysis
    Antel, SB
    Collins, DL
    Bernasconi, N
    Andermann, F
    Shinghal, R
    Kearney, RE
    Arnold, DL
    Bernasconi, A
    [J]. NEUROIMAGE, 2003, 19 (04) : 1748 - 1759
  • [2] Computational models of MRI characteristics of focal cortical dysplasia improve lesion detection
    Antel, SB
    Bernasconi, A
    Bernasconi, N
    Collins, DL
    Kearney, RE
    Shinghal, R
    Arnold, DL
    [J]. NEUROIMAGE, 2002, 17 (04) : 1755 - 1760
  • [3] Fully automatic segmentation of the brain in MRI
    Atkins, MS
    Mackiewich, BT
    [J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 1998, 17 (01) : 98 - 107
  • [4] Optimized homomorphic unsharp masking for MR grayscale inhomogeneity correction
    Brinkmann, BH
    Manduca, A
    Robb, RA
    [J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 1998, 17 (02) : 161 - 171
  • [5] Voxel-based morphometry in the detection of dysplasia and neoplasia in childhood epilepsy: Combined grey/white matter analysis augments detection
    Bruggemann, Jason M.
    Wilke, Marko
    Som, Seu S.
    Bye, Ann M. E.
    Bleasel, Andrew
    Lawson, John A.
    [J]. EPILEPSY RESEARCH, 2007, 77 (2-3) : 93 - 101
  • [6] CESARONI E, 2005, P 14 M WORLD SOC STE, V14, P14
  • [7] Segmentation of focal cortical dysplasia lesions on MRI using level set evolution
    Colliot, O.
    Mansi, T.
    Bernasconi, N.
    Naessens, V.
    Klironomos, D.
    Bernasconi, A.
    [J]. NEUROIMAGE, 2006, 32 (04) : 1621 - 1630
  • [8] Individual voxel-based analysis of gray matter in focal cortical dysplasia
    Colliot, O
    Bernasconi, N
    Khalili, N
    Antel, SB
    Naessens, V
    Bernasconi, A
    [J]. NEUROIMAGE, 2006, 29 (01) : 162 - 171
  • [9] Colliot O, 2006, I S BIOMED IMAGING, P323
  • [10] Segmentation of skull and scalp in 3-D human MRI using mathematical morphology
    Dogdas, B
    Shattuck, DW
    Leahy, RM
    [J]. HUMAN BRAIN MAPPING, 2005, 26 (04) : 273 - 285