FreeSurfer-Introduction

2019-10-31  本文已影响0人  SnorlaxSE

【摘要】FreeSurfer - Cortical surface and subcortical modelling 皮层表面和皮质下建模

Installation

Test your FreeSurfer Installation

FreeSurfer Tutorials

基本指令说明

$ recon-all

详解

USAGE: recon-all

 Required Arguments:
   -subjid <subjid>
   -<process directive>

 Fully-Automated Directive:
  -all           : performs all stages of cortical reconstruction
  -autorecon-all : same as -all

 Manual-Intervention Workflow Directives:
  -autorecon1    : process stages 1-5 (see below)  # no-use-gpu: about 10 min
  -autorecon2    : process stages 6-23
                   after autorecon2, check white surfaces:
                     a. if wm edit was required, then run -autorecon2-wm
                     b. if control points added, then run -autorecon2-cp
                     c. proceed to run -autorecon3
  -autorecon2-cp : process stages 12-23 (uses -f w/ mri_normalize, -keep w/ mri_seg)
  -autorecon2-wm : process stages 15-23
  -autorecon2-inflate1 : 6-18
  -autorecon2-perhemi : tess, sm1, inf1, q, fix, sm2, inf2, finalsurf, ribbon
  -autorecon3    : process stages 24-34
                     if edits made to correct pial, then run -autorecon-pial
  -hemi ?h       : just do lh or rh (default is to do both)

  Autorecon Processing Stages (see -autorecon# flags above):
    1.  Motion Correction and Conform  # 运动校正和一致
    2.  NU (Non-Uniform intensity normalization)  # 非均匀强度归一化
    3.  Talairach transform computation  #  Talairach变换计算
    4.  Intensity Normalization 1  # 强度归一化
    5.  Skull Strip  # 颅骨去除   

    6.  EM Register (linear volumetric registration)  # EM寄存器（线性体积配准）
    7.  CA Intensity Normalization  # CA强度归一化
    8.  CA Non-linear Volumetric Registration  # CA非线性体积配准
    9.  Remove neck  # 去除颈部
    10. EM Register, with skull  # EM注册，带头骨
    11. CA Label (Aseg: Volumetric Labeling) and Statistics  # CA标签（Aseg：体积标签）和统计

    12. Intensity Normalization 2 (start here for control points) # 强度归一化2（从控制点开始）
    13. White matter segmentation  # 白质细分
    14. Edit WM With ASeg  # 使用ASeg编辑WM
    15. Fill (start here for wm edits)  # 填充（从这里开始编辑wm）
    16. Tessellation (begins per-hemisphere operations)  # 曲面细分（每半球操作开始）
    17. Smooth1
    18. Inflate1
    19. QSphere
    20. Automatic Topology Fixer  # 自动拓扑修复器
    21. White Surfs (start here for brain edits for pial surf)  # 白色Surfs（从这里开始用于脑部冲浪的大脑编辑）
    22. Smooth2
    23. Inflate2

    24. Spherical Mapping  # 球面映射
    25. Spherical Registration  # 球形配准
    26. Spherical Registration, Contralater hemisphere  # 球面配准，Contralater半球
    27. Map average curvature to subject  # 将平均曲率映射到主题
    28. Cortical Parcellation (Labeling)  # 皮质分割（标签）
    29. Cortical Parcellation Statistics  # 皮质分割统计
    30. Pial Surfs  # Pial Surfs
    31. WM/GM Contrast  # WM / GM对比
    32. Cortical Ribbon Mask  # 皮质功能掩膜
    33. Cortical Parcellation mapped to ASeg  # Cortical Parcellation映射到ASeg
    34  Brodmann and exvio EC labels  # Brodmann和exvio EC标签

 Step-wise Directives
  See -help
    ...

$ mri_convert

mri_convert.bin 
                Help

NAME
    mri_convert

SYNOPSIS
    mri_convert [options] <in volume> <out volume>

DESCRIPTION
    mri_convert is a general purpose utility for converting between 
    different file formats. The file type can be specified in two ways. 
    First, mri_convert will try to figure it out on its own from the 
    format of the file name (eg, files that end in .img are assumed to be 
    in spm analyze format). Second, the user can explicity set the type of
    file using --in_type and/or --out_type.
    
    Legal values for --in_tye (-it) and --out_type (-ot) are listed under 
    optional flagged arguments.

$ preproc-cess

FS-FAST Preprocessing

USAGE: preproc-sess

  -per-run : motion cor and reg to middle TP of each run
  -per-session : motion cor and reg to 1st TP of 1st run
  -fwhm FWHM : smoothing level (mm)

  -update        : only run a stage if input is newer than output (default)
  -force         : force reprocessing of all stages (turns off -update)
  -no-update     : same as -force
  -sliceorder so : turn on slice timing correction (STC) with the given slice order
  -ngroups nSliceGroups : number of SMS slice groups for STC
  -surface subject hemi : set hemi to lhrh to do both
  -mni305-2mm    : sample raw data to mni305 at 2mm (same as -mni305)  # useful
  -mni305-1mm    : sample raw data to mni305 at 1mm
  -cvs : sample raw data to cvs_avg35_inMNI152 at 2mm (not with -mni305)

Session Arguments (some combination required)
  -sf sessidfile  ...
  -df srchdirfile ...
  -s  sessid      ...
  -d  srchdir     ...
  -fsd    fsd <bold>
  -rlf    rlf  : run list file (default all runs)

  -init-fsl : use fsl to initialize bbr registration
  -init-spm : use spm to initialize bbr registration (needs matlab)
  -init-header : use geometry to initialize bbr registration
  -bbr-int ifsd istem : use intermediate volume in sess/ifsd/RRR/istem

Other options (probably not too useful)

  -nomc     : don't do motion correction
  -nostc    : don't do slice-timing correction
  -nosmooth : don't do smoothing
  -nomask   : don't create brain mask
  -noreg    : don't do registration
  -noinorm  : don't do inorm
  -no-subcort-mask : do not apply subcortical masking

  -mcin   mcinstem    : stem to use as input  to MC
  -mcout  mcoutstem   : stem to use as output of MC
  -stcin  stcinstem   : stem to use as input  to STC 
  -stcout stcoutstem  : stem to use as output of STC 
  -smin   sminstem    : stem to use as input  to smoothing 
  -smout  sminstem    : stem to use as output of smoothing 
  -mask   maskstem    : <brain>

  -i    instem    : stem to use as overal input <f>
    
    -regfile regfile   : registration file for use with -surf-fwhm (register.dat)
  -projfrac frac : projection fraction for use with -surf-fwhm (0.5)
  -projfrac-avg  : average over ribbon (not with -projfrac)
  -no-cortex-label : do not use cortex label for masking surfaces

Once the data have been arranged in the proper directory structure and naming convention, they are ready to be preprocessed. Preprocessing includes：

1. Template Creation
2. Brain Mask Creation
3. Registration with FreeSurfer Anatomical
4. Motion Correction
5. Slice Timing Correction (if using)
6. Spatial Normalization
7. Masking
8. Spatial Smoothing   # useful

扩展阅读

Fixing a bad skull strip

FsFastTutorialV6.0

mris_ca_train 从一组带注释的主题创建地图集、mris_ca_label 对于单个主题，生成一个注释文件，其中每个皮质表面顶点都分配有一个神经解剖标签、mris_sample_parc 采样

应用场景

颅骨去除

Linux Freesurfer脑数据分割：

mri_watershed -T1 -t 20 input_file output_file

命令行，经过试验，加入-T1会避免由于原图的灰度值范围不对导致的报错，也可以更干净地去除脑壳，阈值选20（加入-T1比不加去得更干净）,但可能会误剔除，需测试后再进行批处理操作。

对比：两种方法效果基本一致，recon-all提取的输出细节更细腻一点

预处理分割

after-autorecon1, -autorecon2 includes 白质分割、皮下组织分割

Multimodal Integration

FAQ

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