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Analysis of DICOM Image Compression Alternative Using Huffman Coding.

Romi Fadillah Rahmat1, T S M Andreas1, Fahmi Fahmi2

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Huffman coding, a lossless compression method, effectively reduces Digital Imaging and Communication in Medicine (DICOM) file sizes. This technique offers significant space savings and fast compression/decompression for medical images in open Picture Archiving and Communication Systems (PACS).

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Area of Science:

  • Medical Imaging Informatics
  • Data Compression Algorithms
  • Health Informatics

Background:

  • Digital Imaging and Communication in Medicine (DICOM) is a standard for medical image storage.
  • Increasing medical image data necessitates efficient storage and transmission solutions.
  • Current methods face challenges in balancing compression, speed, and security for large datasets.

Purpose of the Study:

  • To evaluate Huffman coding as a lossless compression technique for DICOM files.
  • To analyze the performance of Huffman coding in open Picture Archiving and Communication Systems (PACS).
  • To assess compression ratio, speed, and security aspects of Huffman coding for medical images.

Main Methods:

  • The study applied Huffman coding, a lossless compression algorithm based on byte frequency distribution.
  • Experiments were conducted using various types of DICOM images.
  • Performance metrics included compression ratio, compression/decompression time, and security analysis.

Main Results:

  • Huffman coding achieved a compression ratio of up to 1:3.7010.
  • The technique resulted in space savings of up to 72.98%.
  • Analysis covered compression/decompression times and security implications.

Conclusions:

  • Huffman coding is a viable lossless compression method for DICOM files.
  • It offers substantial space savings and efficient performance for medical image data.
  • The method is suitable for open PACS environments requiring fast and secure image sharing.