feat(apps): add impact-reg-konfai registration orchestrator

apps/impact_reg/.gitignore

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+build/
+impact_reg_konfai.egg-info/

apps/impact_reg/LICENSE

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apps/impact_reg/README.md

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+[![License](https://img.shields.io/badge/license-Apache%202.0-green.svg)](https://www.apache.org/licenses/LICENSE-2.0)
+[![PyPI version](https://img.shields.io/pypi/v/impact_reg_konfai.svg?color=blue)](https://pypi.org/project/impact_reg_konfai/)
+[![Python](https://img.shields.io/badge/python-3.10%2B-blue.svg)](https://www.python.org/)
+[![CI](https://github.com/vboussot/KonfAI/actions/workflows/konfai_ci.yml/badge.svg)](https://github.com/vboussot/KonfAI/actions/workflows/konfai_ci.yml)
+[![Paper](https://img.shields.io/badge/📌%20Paper-KonfAI-blue)](https://www.arxiv.org/abs/2508.09823)
+
+<p align="center">
+  <img src="Logo.png" alt="IMPACT-Reg logo" width="220">
+</p>
+
+# IMPACT-Reg-KonfAI
+
+**Fast and lightweight CLI for multimodal medical image registration using IMPACT-Reg presets within the KonfAI framework.**
+
+---
+
+## 🧩 Overview
+
+**IMPACT-Reg-KonfAI** is the **command-line interface (CLI)** for running **IMPACT-Reg** registration presets published
+in the [`VBoussot/ImpactReg`](https://huggingface.co/VBoussot/ImpactReg) Hugging Face repository, through the
+[KonfAI](https://github.com/vboussot/KonfAI) deep learning framework.
+
+**IMPACT-Reg** introduces a **semantic similarity metric** for **multimodal registration**, driven by deep features
+extracted from large pretrained segmentation and foundation models (MIND, TotalSegmentator, MRSegmentator). It plugs
+into an Elastix-based multi-resolution deformable pipeline to achieve robust cross-modality alignment while keeping
+deformations smooth and physically plausible.
+
+A registration run combines:
+
+- **fixed** and **moving** images
+- one or more **registration presets** resolved from the published preset database (each preset is a KonfAI app)
+- optional **image**, **segmentation**, or **landmark** references (with an optional mask) for evaluation
+
+---
+
+## 🧠 Features
+
+- ⚡ **Fast registration** powered by [KonfAI](https://github.com/vboussot/KonfAI)
+- 🤗 **Automatic preset, parameter-map, and model download** from Hugging Face
+- 🧩 **Multi-preset ensembling** (transforms averaged into a single displacement field)
+- 🧠 **Semantic IMPACT metric** on deep features from pretrained segmentation / foundation models
+- 📐 **Evaluation workflows** against image, segmentation, and landmark references
+- 🧾 **Multi-format compatibility:** supports all major medical image formats handled by ITK
+
+---
+
+## 🗂️ Available presets
+
+Presets are resolved dynamically from the published preset database (`PresetDatabase.json`) and passed as the first
+positional argument(s). Current presets include generic rigid / rigid + BSpline strategies and IMPACT-driven
+deformable presets tuned per modality pair (MR/CT, CBCT/CT) and anatomy (generic, head & neck).
+
+List the presets exposed by your installation with:
+
+```bash
+impact-reg-konfai register --help
+```
+
+---
+
+## 🚀 Installation
+
+From PyPI:
+
+```bash
+python -m pip install impact-reg-konfai
+```
+
+From source:
+
+```bash
+git clone https://github.com/vboussot/KonfAI.git
+python -m pip install -e apps/impact_reg
+```
+
+---
+
+## ⚙️ Usage
+
+The CLI is organised into sub-commands, matching the registration workflow:
+
+| Sub-command | Purpose |
+|---|---|
+| `register` | Register a moving image onto a fixed image with one or more presets. Several presets are ensembled (their displacement fields are averaged). Writes the moved image, the displacement field (`DVF`), the transform, and the per-preset fields (kept for `uncertainty`). |
+| `eval` | Evaluate a registration on any subset of modalities — image (MAE), segmentation (Dice), landmarks (TRE). At least one modality is required. |
+| `uncertainty` | Voxel-wise spread map from an ensemble of displacement fields. |
+
+Register a moving image onto a fixed image (ensemble several presets by listing them):
+
+```bash
+impact-reg-konfai register <PRESET> [<PRESET_2> ...] -f fixed.nii.gz -m moving.nii.gz -o ./Output --gpu 0
+```
+
+Evaluate a registration — any subset of modalities; the transform comes from a prior `register`:
+
+```bash
+impact-reg-konfai eval \
+  --transform ./Output/P000/Transform.h5 \
+  -f fixed.nii.gz -m moving.nii.gz --mask roi.nii.gz \
+  --gt-fixed-seg fixed_seg.nii.gz --gt-moving-seg moving_seg.nii.gz \
+  --gt-fixed-fid fixed.fcsv --gt-moving-fid moving.fcsv \
+  -o ./Output --gpu 0
+```
+
+Estimate uncertainty from the per-preset displacement fields written by `register`:
+
+```bash
+impact-reg-konfai uncertainty --dvf ./Output/P000/Ensemble/*.mha -o ./Output/P000
+```
+
+### `register` arguments
+
+| Flag | Description | Default |
+|------|-------------|---------|
+| `PRESET` | One or more presets from the published preset database (several are ensembled) | *required* |
+| `-f`, `--fixed-images` | Fixed image(s), or a dataset directory | *required* |
+| `-m`, `--moving-images` | Moving image(s), or a dataset directory | *required* |
+| `-o`, `--output` | Output directory | `./Output/` |
+| `--gpu` / `--cpu` | GPU id(s) / CPU worker processes | CPU if unset |
+| `-q`, `--quiet` | Suppress console output | `False` |
+
+### `eval` arguments — at least one modality required
+
+| Flag | Description | Default |
+|------|-------------|---------|
+| `--transform` | Transform(s) from a prior `register` (identity if omitted) | *unset* |
+| `-f`, `-m` | Fixed / moving images — image modality (MAE) | *unset* |
+| `--gt-fixed-seg`, `--gt-moving-seg` | Fixed / moving segmentations — seg modality (Dice) | *unset* |
+| `--gt-fixed-fid`, `--gt-moving-fid` | Fixed / moving landmarks — fid modality (TRE) | *unset* |
+| `--mask` | Evaluation mask(s) for the image modality | *unset* |
+| `--preset` | Preset providing the evaluation configs | first available |
+
+### `uncertainty` arguments
+
+| Flag | Description | Default |
+|------|-------------|---------|
+| `--dvf` | Two or more ensemble displacement fields (e.g. the per-preset fields from `register`) | *required* |
+| `-o`, `--output` | Output directory | `./Output/` |
+
+See the full help of any sub-command with:
+
+```bash
+impact-reg-konfai register --help
+```
+
+---
+
+## 📦 Notes
+
+- Available presets are resolved dynamically from the published IMPACT-Reg preset database.
+- Multiple presets can be provided in one command; their displacement fields are averaged into a single field.
+- The wrapper orchestrates the preset KonfAI apps (model inference), then ensembles, evaluates, and estimates uncertainty on their outputs.
+
+---
+
+## 📚 References
+
+If you use **IMPACT-Reg-KonfAI** in your work, please cite KonfAI and the IMPACT-Reg paper.
+
+- Boussot, V., Hémon, C., Nunes, J.-C., Dowling, J., Rouzé, S., Lafond, C., Barateau, A., & Dillenseger, J.-L.
+  **IMPACT-Reg: A Generic Semantic Loss for Multimodal Medical Image Registration.**
+
+- Boussot, V., & Dillenseger, J.-L. (2025).
+  **KonfAI: A Modular and Fully Configurable Framework for Deep Learning in Medical Imaging.**
+  arXiv preprint [arXiv:2508.09823](https://arxiv.org/abs/2508.09823)
+
+---
+
+## 🔗 Links
+
+- 🤗 **Model Hub:** [huggingface.co/VBoussot/ImpactReg](https://huggingface.co/VBoussot/ImpactReg)
+- 📦 **PyPI Package:** [pypi.org/project/impact_reg_konfai](https://pypi.org/project/impact_reg_konfai)
+- 🧠 **KonfAI Repository:** [github.com/vboussot/KonfAI](https://github.com/vboussot/KonfAI)

apps/impact_reg/impact_reg_konfai/__init__.py

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+"""Python package for the IMPACT-Reg KonfAI app wrapper."""