medimgkit 0.15.0

A comprehensive toolkit for medical image processing, including DICOM, NIfTI, and multi-format I/O utilities

MedImgKit

A comprehensive toolkit for medical image processing, providing utilities for DICOM, NIfTI, and other medical image formats with seamless multi-format I/O operations.

Features

• DICOM Support: Read, anonymize, and manipulate DICOM files
• NIfTI Support: Work with neuroimaging data in NIfTI format
• Multi-format I/O: Unified interface for reading various image formats
• Anonymization: DICOM anonymization following DICOM standards
• Coordinate Conversion: Convert between pixel and patient coordinates
• Multi-frame Assembly: Combine multiple DICOM files into multi-frame volumes

Installation

From PyPI

pip install medimgkit

From Source

pip install git+https://github.com/SonanceAI/medimgkit

Quick Start

DICOM Operations

import medimgkit as mik
import pydicom

# Read and normalize DICOM image
ds = pydicom.dcmread('path/to/dicom.dcm')
image_array = mik.load_image_normalized(ds)

# Anonymize DICOM
anonymized_ds = mik.anonymize_dicom(ds)

# Convert pixel coordinates to patient coordinates
patient_coords = mik.pixel_to_patient(ds, pixel_x=100, pixel_y=150)

NIfTI Operations

import nibabel as nib
import medimgkit as mik
from medimgkit.nifti_utils import read_nifti_slice

# Load NIfTI file
nifti_data = nib.load('path/to/image.nii.gz')

# Get a specific slice
slice_image = mik.get_slice(nifti_data, slice_index=50, slice_axis=2)

# Read a slice by anatomical plane while preserving native slice orientation
slice_image, nifti_img = read_nifti_slice(
	'path/to/image.nii.gz',
	slice_index=50,
	plane='coronal',
)

# Convert world coordinates to slice index
slice_idx, axis = mik.line_to_slice_index(nifti_data, point1, point2)

Multi-format Reading

import medimgkit as mik

# Read any supported format
image_array = mik.read_array_normalized('path/to/image.dcm')
image_array = mik.read_array_normalized('path/to/image.nii.gz')
image_array = mik.read_array_normalized('path/to/image.png')

API Reference

DICOM Utils (medimgkit.dicom_utils)

Core Functions

• load_image_normalized(dicom, index=None): Load and normalize DICOM pixel data
• anonymize_dicom(ds, retain_codes=[], copy=False, token_mapper=None): Anonymize DICOM following standards
• assemble_dicoms(files_path, return_as_IO=False): Combine multiple DICOMs into multi-frame
• is_dicom(f): Check if file is a DICOM

Coordinate Conversion

• pixel_to_patient(ds, pixel_x, pixel_y, slice_index=None): Convert pixel to patient coordinates
• get_image_position(ds, slice_index=None): Get image position in patient coordinates
• get_pixel_spacing(ds, slice_index): Get pixel spacing information

Anatomical Analysis

• determine_anatomical_plane_from_dicom(ds, slice_axis, alignment_threshold=0.95): Determine anatomical plane

NIfTI Utils (medimgkit.nifti_utils)

Slice Operations

• get_slice(data, slice_index, slice_axis=None, plane=None): Extract a slice from a 3D/4D volume
• read_nifti_slice(file_path, slice_index, plane=None): Read one standardized slice in (C, H, W) format while preserving native orientation
• get_slice_from_line(data, world_point1, world_point2): Get slice defined by line
• slice_location_to_slice_index(data, slice_location, slice_axis): Convert location to index

Coordinate Conversion

• line_to_slice_index(data, world_point1=None, world_point2=None, coplanar_vector=None): Convert line to slice
• axis_name_to_axis_index(data, axis_name): Convert axis name to index

Utilities

• is_nifti_file(file_path): Check if file is NIfTI format

I/O Utils (medimgkit.io_utils)

Reading Functions

• read_array_normalized(file_path, index=None, return_metainfo=False, use_magic=False): Universal image reader
• read_image(file_path): Read standard image formats (PNG, JPEG)
• read_nifti(file_path, mimetype=None, slice_index=None, plane=None): Read NIfTI files and optionally order slices by anatomical plane
• read_video(file_path, index=None): Read video files

Supported Formats

• DICOM: .dcm, .dicom (and files without extension)
• NIfTI: .nii, .nii.gz
• Images: .png, .jpg, .jpeg
• Video: .mp4, .avi, .mov, .mkv
• NumPy: .npy

Development

Running Tests

pytest

License

MIT License - see LICENSE file for details.

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request