/Dicom-PDF

This module is designed to streamline the process of handling medical images by automating the download of DICOM files from an Orthanc server, converting these files into standard image formats, and compiling the images into a grid layout within a PDF document.

Primary LanguagePython

Ultrasound DICOM Image to PDF

Project Overview

This project processes ultrasound DICOM files, extracts and converts them into images! The process finishes with a 4x2 (8 images) grid layout pdf file page. ALso, in Obstetrical Exams you can create growth charts. It combines image processing with advanced biometrical analysis to provide a complete view of fetal development.

Key Components

1. DICOM Processing (DicomManager/DICOM.py)

  • Class: DICOM2JPEG
    • Converts DICOM files to JPEG format
    • Enhances image quality (contrast, brightness, sharpness)
    • Identifies and separates Structured Report (SR) DICOM files

2. Biometrical Data Extraction (SR/SR2DATA.py)

  • Function: ExtractSR

    • Extracts biometrical measurements from DICOM SR files
    • Processes key measurements: Head Circumference, Biparietal Diameter, Abdominal Circumference, Femur Length, Estimated Fetal Weight

  • Function: pdf_report

    • Generates a PDF report containing measurement data and growth charts
    • Organizes plots in a two-per-page layout

3. Growth Chart Generation (SR/SR2PLOT.py)

  • Function: create_other_plots
    • Creates individual growth charts for each biometric measurement
    • Plots patient data against standard percentile curves (10th, 50th, 90th)
    • Uses a dark theme for better visibility

4. PDF Generation (PDFMAKER/pdfmaker.py)

  • Class: MkPDF
    • Creates a grid layout of ultrasound images
    • Incorporates biometrical data and growth charts into the report

5. Main Execution (main.py)

  • Orchestrates the entire process:
    • Unzips DICOM files
    • Converts DICOM to JPEG
    • Extracts biometrical data
    • Generates growth charts
    • Creates the final PDF report

Workflow

  1. DICOM Extraction: Unzip and organize DICOM files
  2. Image Conversion: Convert DICOM images to JPEG format
  3. Data Extraction: Extract biometrical data from SR DICOM files
  4. Chart Generation: Create growth charts for each biometric measurement
  5. Report Compilation: Generate a PDF report with images, measurements, and charts
  6. PDF Merging: Combine multiple PDFs if necessary

Key Features

  1. Comprehensive Data Processing: Handles both image and structured report DICOM files
  2. Enhanced Visualization: Improves ultrasound image quality for better analysis
  3. Biometrical Analysis: Extracts and visualizes key fetal measurements
  4. Growth Assessment: Plots fetal measurements against standard growth curves
  5. Customized Reporting: Generates professional PDF reports with images and charts

Technical Details

Libraries Used

  • pydicom: For reading DICOM files
  • Pillow (PIL): For image processing
  • matplotlib: For creating growth charts
  • reportlab: For generating PDF reports
  • numpy: For numerical operations
  • scipy: For interpolation in growth charts

Data Processing

  • Extracts and processes various fetal measurements:
    • Head Circumference (HC)
    • Biparietal Diameter (BPD)
    • Abdominal Circumference (AC)
    • Femur Length (FL)
    • Estimated Fetal Weight (EFW)

Visualization

  • Growth charts use a dark theme for better contrast
  • Each chart includes 10th, 50th, and 90th percentile lines
  • Patient's specific measurement is highlighted on each chart

PDF Generation

  • Combines ultrasound images in a grid layout
  • Includes a summary of all biometrical measurements
  • Presents growth charts for each measurement
  • Optimized for A4 paper size

Future Improvements

  1. Implement machine learning for automated measurement verification
  2. Add support for 3D/4D ultrasound data
  3. Develop a user-friendly interface for easier operation
  4. Integrate with hospital information systems for seamless data flow
  5. Implement multi-language support for international use

Conclusion

This project provides a comprehensive solution for processing fetal ultrasound data, combining image analysis with advanced biometrical assessments. It offers healthcare professionals a powerful tool for monitoring fetal growth and development, enhancing the quality of prenatal care.

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