git:20260325.6f1b393 to git:20260325.72d2cbf

49 added, 71 removed. Audit A to A.

---

name: fsl-tool

description: "Use this skill whenever the user wants to process neuroimaging data with FSL (FMRIB Software Library), covering structural MRI, functional MRI (fMRI), and diffusion MRI (dMRI/DTI). Triggers include: 'use FSL', 'FSL processing', 'fsl_anat', 'FEAT', 'MELODIC', 'eddy', 'bedpostx', 'probtrackx', 'BET', 'FAST', 'FLIRT', 'FNIRT', 'run FSL pipeline'. This skill is the NeuroClaw interface-layer wrapper for FSL: checks installation, generates execution plan with concrete shell commands, waits for explicit confirmation, then routes all commands through claw-shell."

license: MIT License (NeuroClaw custom skill – freely modifiable within the project)

---

- # FSL Tool (FMRIB Software Library)

+ # FSL Tool

## Overview

FSL is a comprehensive library of analysis tools for MRI, fMRI, and diffusion brain imaging. This skill provides a safe, unified interface for the three core modalities in NeuroClaw:

- - Structural MRI (T1w, T2w, FLAIR)

- - Functional MRI (task-based and resting-state)

+ - Structural MRI (T1w, T2w, FLAIR)

+ - Functional MRI (task-based and resting-state)

- Diffusion MRI (DTI / dMRI)

**Workflow**:

- 1. Check if FSL is installed (`fslversion`).

- 2. If not installed → call `dependency-planner` to generate installation plan.

- 3. Analyze input files and propose concrete shell commands with parameter explanations.

- 4. Present full numbered plan + estimated time + risks.

- 5. Wait for explicit user confirmation (“YES”, “execute”, “proceed”).

- 6. Execute all commands safely via `claw-shell`.

+ 1. Check if FSL is installed (`fslversion`).

+ 2. If not installed → call `dependency-planner` to generate installation plan.

+ 3. Analyze input files and propose concrete shell commands with parameter explanations.

+ 4. Present full numbered plan + estimated time + risks.

+ 5. Wait for explicit user confirmation (“YES”, “execute”, “proceed”).

+ 6. Execute all commands safely via `claw-shell`.

7. Summarize outputs and suggest next steps.

**Research use only.**

## Core Modalities and Common Shell Commands

### 1. Structural MRI

```bash

# One-click structural preprocessing (strongly recommended)

fsl_anat -i T1w.nii.gz -o T1w_anat --clobber

- # -i : 输入 T1w 文件

- # -o : 输出文件夹名称

- # --clobber : 覆盖已存在文件（常用）

+ # -i : input T1w file

+ # -o : output folder name

+ # --clobber : overwrite existing files (commonly used)

# Brain extraction (BET)

bet T1w.nii.gz T1w_brain -m -f 0.5

- # -m : 输出脑掩膜（_mask.nii.gz）

- # -f : 脑提取阈值（0.3~0.7，越小保留越多脑组织，通常 0.5 较稳妥）

+ # -m : output brain mask (_mask.nii.gz)

+ # -f : brain extraction threshold (0.3~0.7; 0.5 is usually stable)

# Tissue segmentation + bias correction

fast -t 1 -n 3 -H 0.1 -I 4 -l 20.0 -o T1w_fast T1w_brain

- # -t 1 : T1 加权图像

- # -n 3 : 分成 3 类（灰质、白质、脑脊液）

- # -H 0.1 : 偏场校正强度（0.0~0.4，越大校正越强）

- # -o : 输出前缀

+ # -t 1 : T1-weighted image

+ # -n 3 : 3 tissue classes (GM, WM, CSF)

+ # -H 0.1 : bias field correction strength

# Linear + nonlinear registration to MNI152

flirt -in T1w_brain -ref $FSLDIR/data/standard/MNI152_T1_2mm_brain -out T1w_to_MNI -omat T1w_to_MNI.mat -dof 12

- # -dof 12 : 12 参数仿射配准（常用）

fnirt --in=T1w_brain --aff=T1w_to_MNI.mat --cout=T1w_to_MNI_warp --config=T1_2_MNI152_2mm

- # --config : 使用标准配置文件（2mm 分辨率最常用）

# Subcortical segmentation

first -i T1w_brain -o T1w_first -b

- # -b : 输出所有亚皮层结构的二值化掩膜

```

### 2. Functional MRI

```bash

# Motion correction

mcflirt -in bold.nii.gz -out bold_mcf -plots -refvol 0

- # -plots : 输出运动参数图

- # -refvol 0 : 以第 0 帧作为参考（常用）

# Task-based fMRI full analysis (FEAT)

feat design.fsf

- # 需要提前准备 design.fsf 文件（可通过 FEAT GUI 生成）

# Resting-state ICA

melodic -i bold_mcf.nii.gz -o melodic_output --report --nobet --bgthreshold=10 --tr=2.0 --mmthresh=0.5 --dim=30

- # --tr : 重复时间（秒），必须与实际扫描一致

- # --dim : 估计的独立成分数量（20~50 较常用）

- # --report : 生成 HTML 报告（强烈推荐）

# Automatic denoising (FIX)

fix melodic_output -c $FSLDIR/training_files/Standard.RData -m -f 20

- # -c : 分类器文件（Standard.RData 最常用）

- # -f 20 : 运动/噪声阈值（越高越保守，通常 20~30）

```

### 3. Diffusion MRI

```bash

# Distortion and eddy current correction

topup --imain=AP_PA_b0.nii.gz --datain=acqparams.txt --out=topup_results --fout=field --iout=b0_unwarped

eddy --imain=dwi.nii.gz --mask=dwi_brain_mask.nii.gz --acqp=acqparams.txt --index=index.txt \

--bvecs=bvecs --bvals=bvals --topup=topup_results --out=eddy_corrected --very_verbose

- # --very_verbose : 输出详细日志（调试时有用）

# Tensor fitting

dtifit -k eddy_corrected.nii.gz -m dwi_brain_mask.nii.gz -r bvecs -b bvals -o dtifit

- # -k : 校正后的扩散图像

- # -r / -b : 梯度方向和 b 值文件

# Multi-fiber modeling

bedpostx bedpostx_input -n 3 -w 1 -b 1000

- # -n 3 : 每个体素最多 3 根纤维（常用）

- # -b 1000 : 燃烧采样次数（默认 1000，越大越精确但越慢）

# Automated major tract extraction

xtract -bpx bedpostx_input.bedpostX -out xtract_results -str $FSLDIR/data/xtract/tracts.txt

- # -str : 使用的标准白质束列表文件

```

## Quick Reference

- |----------------|-----------------------------|----------------------------------|------------------|

- | Structural | Brain extraction | `bet` | 1–3 min |

+ |--------------|-----------------------------|-------------------------------|-------------------|

+ | Structural | Brain extraction | `bet` | 1–3 min |

## Installation

Use `dependency-planner` skill with one of the following requests:

- - “Install latest FSL on Ubuntu using official installer”

+ - “Install latest FSL on Ubuntu using official installer”

- “Install FSL via conda-forge in a new environment”

After installation, verify with:

```bash

fslversion

echo $FSLDIR

```

## Important Notes & Limitations

- - All actual execution is routed through `claw-shell`.

- - Long-running commands (bedpostx, probtrackx, group FEAT, etc.) run safely in the `claw` tmux session.

- - Always consider running `fsl_anat` first for structural data — it handles BET + FAST + registration automatically.

- - Input must be NIfTI format. Use `dcm2nii` skill first if starting from DICOM.

+ - All actual execution is routed through `claw-shell`.

+ - Long-running commands (bedpostx, probtrackx, group FEAT, etc.) run safely in the `claw` tmux session.

+ - Always consider running `fsl_anat` first for structural data — it handles BET + FAST + registration automatically.

+ - Input must be NIfTI format. Use `dcm2nii` skill first if starting from DICOM.

- Monitor progress with `tail -f` on the log file provided by claw-shell.

## When to Call This Skill

- - After `dcm2nii` conversion

- - When any FSL preprocessing, registration, segmentation or advanced analysis is needed

+ - After `dcm2nii` conversion

+ - When any FSL preprocessing, registration, segmentation or advanced analysis is needed

- Before feeding quantitative results into `paper-writing` or `experiment-controller`

## Complementary / Related Skills

- - `dcm2nii` / `nii2dcm`

- - `dependency-planner`

- - `claw-shell`

- - `freesurfer-processor`

- - `wmh-segmentation`

+ - `dcm2nii` / `nii2dcm`

+ - `dependency-planner`

+ - `claw-shell`

+ - `freesurfer-tool`

+ - `wmh-segmentation`

+ - `fmriprep-tool`

## More Advanced Features

For less common tools (ASL, FABBER, VBM, PALM, custom scripting, etc.), please refer to the official FSL documentation:

- - Official FSL Website: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/

- - Structural tools: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Structural

- - Functional tools: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FEAT

- - Diffusion tools: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FDT

- - Full tool list: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSL

+ - Official FSL Website: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/

+ - Structural tools: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Structural

+ - Functional tools: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FEAT

+ - Diffusion tools: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FDT

+ - Full tool list: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSL

You may use the `multi-search-engine`, `academic-research-hub`, or `arxiv-cli-tools` skill anytime to find the latest FSL tutorials or example pipelines.

---

- Created At: 2026-03-25

- Last Updated At: 2026-03-25

+ Created At: 2026-03-25 00:00 HKT

+ Last Updated At: 2026-03-25 23:56 HKT

Author: Cheng Wang