prefreesurferpipeline学习

本文介绍了一套完整的医学影像预处理流程,包括图像平均、创建无失真结构体积空间、脑组织提取、图像配准及偏差场校正等关键步骤,并详细展示了如何通过特定脚本实现从个体空间到MNI模板空间的配准。
# 1. To average any image repeats (i.e. multiple T1w or T2w images available)
# 2. To create a native, undistorted structural volume space for the subject
     * Subject images in this native space will be distortion corrected
       for gradient and b0 distortions and rigidly aligned to the axes
       of the MNI space. "Native, undistorted structural volume space"
       is sometimes shortened to the "subject's native space" or simply
       "native space".

# 3. To provide an initial robust brain extraction
# 4. To align the T1w and T2w structural images (register them to the native space)
# 5. To perform bias field correction

# 6. To register the subject's native space to the MNI space


个体到模板配准(?)

log_Msg "Performing Atlas Registration to MNI152 (FLIRT and FNIRT)"

${RUN} ${HCPPIPEDIR_PreFS}/AtlasRegistrationToMNI152_FLIRTandFNIRT.sh \
    --workingdir=${AtlasSpaceFolder} \
    --t1=${T1wFolder}/${T1wImage}_acpc_dc \
    --t1rest=${T1wFolder}/${T1wImage}_acpc_dc_restore \
    --t1restbrain=${T1wFolder}/${T1wImage}_acpc_dc_restore_brain \
    --t2=${T1wFolder}/${T2wImage}_acpc_dc \
    --t2rest=${T1wFolder}/${T2wImage}_acpc_dc_restore \
    --t2restbrain=${T1wFolder}/${T2wImage}_acpc_dc_restore_brain \
    --ref=${T1wTemplate} \
    --refbrain=${T1wTemplateBrain} \
    --refmask=${TemplateMask} \
    --ref2mm=${T1wTemplate2mm} \
    --ref2mmmask=${Template2mmMask} \
    --owarp=${AtlasSpaceFolder}/xfms/acpc_dc2standard.nii.gz \
    --oinvwarp=${AtlasSpaceFolder}/xfms/standard2acpc_dc.nii.gz \
    --ot1=${AtlasSpaceFolder}/${T1wImage} \
    --ot1rest=${AtlasSpaceFolder}/${T1wImage}_restore \
    --ot1restbrain=${AtlasSpaceFolder}/${T1wImage}_restore_brain \
    --ot2=${AtlasSpaceFolder}/${T2wImage} \
    --ot2rest=${AtlasSpaceFolder}/${T2wImage}_restore \
    --ot2restbrain=${AtlasSpaceFolder}/${T2wImage}_restore_brain \
    --fnirtconfig=${FNIRTConfig}


评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值