git:20260328.891ed93 to git:20260404.fa7f354

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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)

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# 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)

- 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`.

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 : 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 : 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-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

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

# Subcortical segmentation

first -i T1w_brain -o T1w_first -b

```

### 2. Functional MRI

```bash

# Motion correction

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

# Task-based fMRI full analysis (FEAT)

feat design.fsf

# Resting-state ICA

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

# Automatic denoising (FIX)

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

```

### 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

# Tensor fitting

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

# Multi-fiber modeling

bedpostx bedpostx_input -n 3 -w 1 -b 1000

# Automated major tract extraction

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

```

## Quick Reference

| Modality | Task | Main Command | Typical Time |

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

| Structural | Full preprocessing | `fsl_anat` | 10–40 min |

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

| Structural | Tissue segmentation | `fast` | 5–15 min |

| Functional | Motion correction | `mcflirt` | 2–10 min |

| Functional | Task GLM | `feat` | 15–90 min |

| Functional | Resting-state ICA | `melodic` | 20–120 min |

| Diffusion | Preprocessing | `topup + eddy` | 30–180 min |

| Diffusion | Tensor metrics | `dtifit` | 5–20 min |

| Diffusion | Tractography | `probtrackx2 / xtract` | 30 min – 24 h+ |

## Installation

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

- “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.

- 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

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

## Complementary / Related Skills

- `dependency-planner`

- `claw-shell`

## 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

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.

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