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DOCKER_EXPORT.md

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+# Docker Image Export/Import Instructions
+
+## 1. Save Docker Image to File
+
+After the build completes, save the image as a .tar file:
+
+```bash
+cd /data/usr/ft42/CVIT_XAI/LungRADS_Modeling/CLARITY/PiNS
+docker save medical-imaging/nodule-segmentation:latest -o medical-imaging-nodule-segmentation.tar
+```
+
+## 2. Compress the Image (Optional - Recommended)
+
+Compress the .tar file to save space:
+
+```bash
+gzip medical-imaging-nodule-segmentation.tar
+# This creates: medical-imaging-nodule-segmentation.tar.gz
+```
+
+## 3. Check File Size
+
+```bash
+ls -lh medical-imaging-nodule-segmentation.tar*
+```
+
+## 4. Load Image on Another Machine
+
+To use the saved image on another machine:
+
+```bash
+# If compressed:
+gunzip medical-imaging-nodule-segmentation.tar.gz
+
+# Load the image:
+docker load -i medical-imaging-nodule-segmentation.tar
+
+# Verify it loaded:
+docker images | grep medical-imaging
+```
+
+## 5. Share the Image
+
+You can now share the .tar.gz file:
+- Copy to USB drive
+- Upload to cloud storage
+- Transfer via network
+- Include in project distribution
+
+## File Size Expectations
+
+- Uncompressed .tar: ~1.5-2.0 GB
+- Compressed .tar.gz: ~800MB-1.2GB
+
+## Alternative: Docker Hub (Optional)
+
+You can also push to Docker Hub for easy sharing:
+
+```bash
+# Tag the image
+docker tag medical-imaging/nodule-segmentation:latest ft42/nodule-segmentation:latest
+
+# Push to Docker Hub
+docker push ft42/nodule-segmentation:latest
+```
+
+## Usage After Import
+
+Once loaded, use exactly as before:
+```bash
+./scripts/DLCS24_KNN_2mm_Extend_Seg.sh
+```

DOCKER_SETUP.md

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+# Docker Setup Instructions
+
+## If you need to build the Docker image from scratch:
+
+1. **Create the Dockerfile** (copy from `Dockerfile.example`):
+   ```bash
+   cp Dockerfile.example Dockerfile
+   ```
+
+2. **Build the Docker image**:
+   ```bash
+   docker build -t medical-imaging/nodule-segmentation:latest .
+   ```
+
+3. **Verify the image was created**:
+   ```bash
+   docker images | grep medical-imaging
+   ```
+
+## If the image already exists:
+
+You can check if it exists with:
+```bash
+docker images | grep medical-imaging/nodule-segmentation
+```
+
+If it shows the image, you can directly run the main script:
+```bash
+./scripts/DLCS24_KNN_2mm_Extend_Seg.sh
+```
+
+## Container Management
+
+The script automatically:
+- Removes any existing container with the same name
+- Creates a new container
+- Runs the segmentation pipeline
+- Keeps the container running for potential debugging
+
+To manually clean up containers:
+```bash
+docker rm -f nodule_seg_pipeline
+```
+
+To see running containers:
+```bash
+docker ps
+```
+
+To see all containers (including stopped):
+```bash
+docker ps -a
+```

Dockerfile

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+FROM ubuntu:20.04
+
+# Set environment variables to avoid interactive prompts
+ENV DEBIAN_FRONTEND=noninteractive
+ENV TZ=America/New_York
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    python3 \
+    python3-pip \
+    python3-dev \
+    build-essential \
+    libssl-dev \
+    libffi-dev \
+    python3-setuptools \
+    git \
+    cmake \
+    tzdata \
+    && rm -rf /var/lib/apt/lists/*
+
+# Install Python packages
+RUN pip3 install --no-cache-dir \
+    SimpleITK \
+    pyradiomics \
+    scikit-learn \
+    numpy \
+    pandas \
+    matplotlib \
+    scipy \
+    nibabel
+
+WORKDIR /app
+CMD ["tail", "-f", "/dev/null"]

Dockerfile.example

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+FROM ubuntu:20.04
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    python3 \
+    python3-pip \
+    python3-dev \
+    build-essential \
+    libssl-dev \
+    libffi-dev \
+    python3-setuptools \
+    git \
+    cmake \
+    && rm -rf /var/lib/apt/lists/*
+
+# Install Python packages
+RUN pip3 install --no-cache-dir \
+    SimpleITK \
+    pyradiomics \
+    scikit-learn \
+    numpy \
+    pandas \
+    matplotlib \
+    scipy \
+    nibabel
+
+WORKDIR /app
+CMD ["tail", "-f", "/dev/null"]