Medical Image Compression using Wavelet Transform on Mobile Devices with ROI coding support

Area of Science:

• Medical Informatics
• Image Processing
• Mobile Computing

Background:

• Mobile devices are increasingly used in healthcare for accessing patient data and medical images.
• Efficient network transmission and processing of large medical image files are critical challenges.
• Wavelet transform offers effective image compression for medical imaging applications.

Purpose of the Study:

• To develop and evaluate a Picture Archiving and Communication Systems (PACS) application for mobile devices.
• To enable viewing of DICOM-compliant medical images on mobile platforms.
• To assess the performance of Wavelet compression with ROI coding for medical images on mobile devices.

Main Methods:

• Development of a PACS application for mobile devices supporting DICOM image viewing.
• Implementation of Wavelet compression with Region of Interest (ROI) coding for image data.
• Pilot testing of the application across diverse radio network segments (IEEE 802.11b, GPRS, DVB-H).

Main Results:

• The developed PACS application successfully displays DICOM medical images on mobile devices.
• Wavelet compression demonstrated efficient handling of medical image data, reducing file sizes.
• Initial pilot results show promising performance over heterogeneous wireless networks.

Conclusions:

• Wavelet compression is a viable technique for medical image transmission and display on mobile devices.
• The developed PACS application facilitates improved access to medical imaging data in clinical settings.
• Further optimization and testing are warranted for widespread clinical adoption.