FSL预处理fmri，结合功能结构都提取大脑，结合服务器并行计算

#!/bin/bash

# 错误处理函数
handle_error() {
    local command="$1"
    echo "错误：$command 执行失败于受试者 $subject"
    echo "最后执行的命令: $BASH_COMMAND"
    exit 1
}

# 定义数据路径
data_dir="/home/userroot/FMRI20250227/OLD_DATA"
output_dir="/home/userroot/FMRI20250227/fsl_fmri_pps_ds_250227"
standard_template="/home/userroot/fsl/data/standard/MNI152_T1_2mm_brain.nii.gz"

# 确保输出文件夹存在
mkdir -p "$output_dir" || { echo "无法创建输出目录"; exit 1; }

# 定义预处理参数
TR=2.5
fwhm=6
highpass_cutoff=0.01
lowpass_cutoff=0.1

# 计算时间滤波参数
hp_sigma=$(awk -v TR=$TR -v hpc=$highpass_cutoff 'BEGIN { print (1/(hpc*TR))/2 }')
lp_sigma=$(awk -v TR=$TR -v lpc=$lowpass_cutoff 'BEGIN { print (1/(lpc*TR))/2 }')

# 遍历受试者
for subject_dir in $(find "$data_dir" -mindepth 1 -maxdepth 1 -type d | sort); do
    subject=$(basename "$subject_dir")
    subject_output_dir="$output_dir/$subject"
    
    # 检查是否为有效目录
    if [ ! -d "$subject_dir" ]; then
        echo "跳过非目录文件：$subject"
        continue
    fi
    
    # 创建目录结构
    mkdir -p "${subject_output_dir}"/{func,anat,reg,qc} || { echo "目录创建失败"; continue; }

    # 获取数据文件
    func_data=("$subject_dir"/*_REST.nii.gz)
    struct_data=("$subject_dir"/*_T1.nii.gz)

    # 检查文件数量
    if [ ${#func_data[@]} -ne 1 ]; then
        echo "错误：在 $subject_dir 中找到 ${#func_data[@]} 个功能数据文件"
        continue
    fi
    if [ ${#struct_data[@]} -ne 1 ]; then
        echo "错误：在 $subject_dir 中找到 ${#struct_data[@]} 个结构数据文件"
        continue
    fi

    echo "正在处理受试者：$subject"

    # 1. 删除前四个时间点
    echo "步骤 1/10：删除前四个时间点"
    fslroi "${func_data[0]}" "${subject_output_dir}/func/rest_tm.nii.gz" 4 -1 || handle_error "fslroi"

    # 2. 切片时间校正
    echo "步骤 2/10：切片时间校正"
    slicetimer -i "${subject_output_dir}/func/rest_tm.nii.gz" \
              -o "${subject_output_dir}/func/rest_tm_st.nii.gz" \
              -r $TR --odd || handle_error "slicetimer"

    # 3. 运动校正
    echo "步骤 3/10：运动校正"
    mcflirt -in "${subject_output_dir}/func/rest_tm_st.nii.gz" \
            -out "${subject_output_dir}/func/rest_tm_st_mc" \
            -mats -plots -rmsrel -rmsabs -report -stats || handle_error "mcflirt"

    # 保存运动参数
    mv "${subject_output_dir}/func/rest_tm_st_mc.par" "${subject_output_dir}/qc/motion.par" || { echo "无法移动运动参数文件"; continue; }




    # 4. 计算均值图像
    echo "步骤 4/10：计算功能像均值"
    fslmaths "${subject_output_dir}/func/rest_tm_st_mc.nii.gz" \
             -Tmean "${subject_output_dir}/func/rest_tm_st_mc_mean.nii.gz" || handle_error "fslmaths"

    # 5. 功能像脑提取
    echo "步骤 5.1/10：均值功能像脑提取"
    bet "${subject_output_dir}/func/rest_tm_st_mc_mean.nii.gz" "${subject_output_dir}/func/rest_tm_st_mc_mean_bet.nii.gz" -f 0.3 -g 0.2 || handle_error "bet_rest"


    # 5. 结构像脑提取
    echo "步骤 5.2/10：结构像脑提取"
    bet "${struct_data[0]}" "${subject_output_dir}/anat/T1_brain.nii.gz" \
          -B -R -f 0.5  -g -0.2 \ 

    # 6. 功能像到结构像配准
    echo "步骤 6/10：功能像到结构像配准"
    flirt -in "${subject_output_dir}/func/rest_tm_st_mc_mean_bet.nii.gz" \
          -ref "${subject_output_dir}/anat/T1_brain.nii.gz" \
          -out "${subject_output_dir}/func/rest_st_mc_reg.nii.gz" \
          -omat "${subject_output_dir}/reg/func2anat.mat" \
          -dof 12 -cost normmi \
          -searchrx -30 30 -searchry -30 30 -searchrz -30 30 || handle_error "flirt"

    # 7. 结构像到标准空间线性配准
    echo "步骤 7/10：结构像线性配准"
    flirt -in "${subject_output_dir}/anat/T1_brain.nii.gz" \
          -ref "$standard_template" \
          -out "${subject_output_dir}/reg/T1_lin2mni.nii.gz" \
          -omat "${subject_output_dir}/reg/lin2mni.mat" \
          -dof 12 \
          -interp trilinear || handle_error "flirt"

    # 8. 非线性配准 (FNIRT)
    echo "步骤 8/10：非线性配准"
    fnirt --in="${subject_output_dir}/anat/T1_brain.nii.gz"  \
          --aff="${subject_output_dir}/reg/lin2mni.mat" \
          --ref="$standard_template" \
          --cout="${subject_output_dir}/reg/T1_warpcoef.nii.gz" \
          --config=T1_2_MNI152_2mm \
          --iout="${subject_output_dir}/reg/T1_nlin2mni.nii.gz" || { echo "FNIRT失败"; continue; }

    # 9. 应用变形场到功能数据
    echo "步骤 9/10：应用变形场"
    applywarp --in="${subject_output_dir}/func/rest_tm_st_mc.nii.gz" \
              --ref="$standard_template" \
              --warp="${subject_output_dir}/reg/T1_warpcoef.nii.gz" \
              --out="${subject_output_dir}/func/rest_mni.nii.gz" \
              --premat="${subject_output_dir}/reg/func2anat.mat" \
              --interp=spline --verbose || handle_error "applywarp"

    # 10. 时间滤波和空间平滑
    echo "步骤 10/10：时间滤波和平滑"
    fslmaths "${subject_output_dir}/func/rest_mni.nii.gz" \
             -Tmean "${subject_output_dir}/func/rest_mni_mean.nii.gz" || handle_error "fslmaths"
    
    fslmaths "${subject_output_dir}/func/rest_mni.nii.gz" \
             -bptf $hp_sigma $lp_sigma \
             -add "${subject_output_dir}/func/rest_mni_mean.nii.gz" \
             "${subject_output_dir}/func/rest_mni_filt.nii.gz" || handle_error "fslmaths"
    
    fslmaths "${subject_output_dir}/func/rest_mni_filt.nii.gz" \
             -s $fwhm \
             "${subject_output_dir}/func/rest_mni_filt_sm.nii.gz" || handle_error "fslmaths"
    echo "受试者："$subject" 已处理完"

done

echo "全部处理完成！"

find "/home/userroot/FMRI20250227/OLD_DATA" -mindepth 1 -maxdepth 1 -type d | sort > subjects_list.txt



cat subjects_list.txt | parallel -j 32 bash fsl_fmri_pps_ds_250224.sh {}