Evidence map›Paper›PMID 31316743›Full record

ArticleJournal of healthcare engineering2019

Analysis of DICOM Image Compression Alternative Using Huffman Coding.

Romi Fadillah Rahmat, T S M Andreas, Fahmi Fahmi, Muhammad Fermi Pasha, Mohammed Yahya Alzahrani, Rahmat Budiarto

Abstract read
In one paragraph

Article in Journal of healthcare engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Breaking Barriers in Emerging Biomedical Applications.Entropy (Basel, Switzerland) · 2022
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Romi Fadillah RahmatDepartment of Information Technology, Faculty of Computer Science and Information Technology, Universitas Sumatera Utara, Medan 20155, Indonesia.
T S M AndreasDepartment of Information Technology, Faculty of Computer Science and Information Technology, Universitas Sumatera Utara, Medan 20155, Indonesia.
Fahmi FahmiDepartment of Electrical Engineering, Faculty of Engineering, Universitas Sumatera Utara, Medan 20155, Indonesia.
Muhammad Fermi PashaMalaysia School of Information Technology, Monash University, Bandar Sunway 47500, Malaysia.ORCID 0000-0002-9848-8950
Mohammed Yahya AlzahraniCollege of Computer Science and Information Technology, Albaha University, Al Bahah, Saudi Arabia.ORCID 0000-0002-9726-6088
Rahmat BudiartoCollege of Computer Science and Information Technology, Albaha University, Al Bahah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Compression, in general, aims to reduce file size, with or without decreasing data quality of the original file. Digital Imaging and Communication in Medicine (DICOM) is a medical imaging file standard used to store multiple information such as patient data, imaging procedures, and the image itself. With the rising usage of medical imaging in clinical diagnosis, there is a need for a fast and secure method to share large number of medical images between healthcare practitioners, and compression has always been an option. This work analyses the Huffman coding compression method, one of the lossless compression techniques, as an alternative method to compress a DICOM file in open PACS settings. The idea of the Huffman coding compression method is to provide codeword with less number of bits for the symbol that has a higher value of byte frequency distribution. Experiments using different type of DICOM images are conducted, and the analysis on the performances in terms of compression ratio and compression/decompression time, as well as security, is provided. The experimental results showed that the Huffman coding technique has the capability to compress the DICOM file up to 1 : 3.7010 ratio and up to 72.98% space savings.

Indexed as

Databases, FactualData CompressionDiagnostic ImagingElectronic Health RecordsHumans

Identifiers

PMID31316743
PMCPMC6604420

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.