DICOM to 3D Volume Converter

Overview

A Python tool for converting DICOM series into 3D volume data in MHD or NIfTI format. This tool automatically processes DICOM files, extracts metadata, calculates slice spacing, and generates properly formatted 3D medical images.

Features

✅ Automatic DICOM file detection and sorting by Instance Number
✅ Slice spacing calculation using multiple methods
✅ Comprehensive metadata extraction
✅ Support for both MHD and NIfTI output formats
✅ Proper handling of DICOM rescaling (slope and intercept)
✅ Preservation of spatial information and orientation

Requirements

Python Dependencies

pydicom numpy SimpleITK

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Installation

pip install pydicom numpy SimpleITK
Usage

Command Line Interface

bash
# Convert to MHD format
python dicom_converter.py /path/to/dicom/folder output_volume.mhd

# Convert to NIfTI format
python dicom_converter.py /path/to/dicom/folder output_volume.nii.gz
Parameters

input_folder: Path to folder containing DICOM files (.dcm)
output_file: Output file path (.mhd or .nii.gz)
Processing Pipeline

1. DICOM File Discovery

Scans specified folder for .dcm files
Validates DICOM file integrity
Reports total number of files found
2. Instance Number Sorting

Reads InstanceNumber from DICOM headers
Sorts files in correct slice order
Ensures proper volume reconstruction
3. Metadata Extraction

Extracted Metadata:

Pixel spacing (X, Y dimensions)
Slice spacing (Z dimension)
Image orientation and position
Rows and columns dimensions
Bits allocated and stored
Pixel representation
4. Slice Spacing Calculation

Primary Methods:

SliceLocation Difference: Uses SliceLocation DICOM tag
ImagePositionPatient: Calculates Euclidean distance between slices
Fallback: Defaults to 1.0 mm if calculation fails
5. Volume Data Creation

Reads pixel arrays from all DICOM files
Applies rescaling (slope and intercept) if needed
Stacks slices into 3D volume array
Maintains original data type and values
6. File Export

Supported Formats:

MHD/RAW: MetaImage format with enhanced metadata
NIfTI: Standard neuroimaging format
Output Specifications

MHD Format Features

Proper voxel spacing in all three dimensions
Transform matrix for correct orientation
Anatomical orientation (RAS)
Offset and center of rotation information
NIfTI Format Features

Correct spatial coordinates
Proper voxel dimensions
Compatible with most medical imaging software