# Clinical Imaging

Clinical and physiological imaging analysis.

- Repository: https://github.com/synthetic-sciences/openscience (4321 stars)
- Category: Engineering
- License: MIT license
- Last updated: 2026-10-30
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add synthetic-sciences/openscience --skill clinical-imaging -g -a claude-code -y`
Codex: `npx skills add synthetic-sciences/openscience --skill clinical-imaging -g -a codex -y`
Cursor: `npx skills add synthetic-sciences/openscience --skill clinical-imaging -g -a cursor -y`
Gemini CLI: `npx skills add synthetic-sciences/openscience --skill clinical-imaging -g -a gemini-cli -y`

## Description

Clinical and physiological imaging analysis. Diffusion MRI ADC maps, micro-CT bone morphometry, hemodynamic parameter analysis, circadian rhythm cosinor analysis, ciliary beat frequency (FFT), and tissue deformation optical flow. For DICOM file handling use pydicom; for biosignals use neurokit2.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Clinical Imaging: Clinical & Physiological Imaging Analysis

## Overview

Clinical Imaging provides computational tools for analyzing clinical and physiological imaging data. This skill covers diffusion MRI apparent diffusion coefficient (ADC) map computation, micro-CT bone morphometry (BV/TV, trabecular thickness), hemodynamic parameter analysis from blood pressure waveforms, circadian rhythm cosinor analysis, ciliary beat frequency measurement via FFT, tissue deformation analysis using optical flow, and amyloid plaque quantification from fluorescence microscopy.

## When to Use This Skill

- Computing ADC maps from multi-b-value diffusion MRI data
- Analyzing bone microarchitecture from micro-CT volumes
- Processing blood pressure or hemodynamic waveform data
- Fitting circadian rhythm data with cosinor models
- Measuring ciliary beat frequency from high-speed video
- Quantifying tissue deformation from image sequences
- Counting and measuring amyloid plaques in fluorescence images

**Related Skills:** For DICOM file handling use `pydicom`. For biosignal processing (ECG, EMG, EDA) use `neurokit2`. For general image analysis use `bioimage-analysis`.

## Installation

```bash
uv pip install nibabel SimpleITK scipy opencv-python scikit-image numpy pandas matplotlib
```

## Quick Start

```python
import numpy as np
from scipy.optimize import curve_fit

# Circadian rhythm cosinor analysis
def cosinor(t, mesor, amplitude, acrophase, period=24):
    return mesor + amplitude * np.cos(2 * np.pi * t / period + acrophase)

# Example: body temperature over 48 hours
time_hours = np.arange(0, 48, 1)
temperature = 36.8 + 0.3 * np.cos(2 * np.pi * time_hours / 24 - 1.0) + \
              np.random.normal(0, 0.1, len(time_hours))

The rest: https://github.com/synthetic-sciences/openscience/blob/HEAD/backend/cli/skills/biology/clinical-imaging/SKILL.md