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

Project description

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

# 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)

# 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): Extract 2D slice from 3D volume
  • 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): Read NIfTI files
  • 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

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