Evidence map›Paper›PMID 30244385›Full record

ArticleJournal of medical systems2018

Medical Image Security Using Dual Encryption with Oppositional Based Optimization Algorithm.

T Avudaiappan, R Balasubramanian, S Sundara Pandiyan, M Saravanan, S K Lakshmanaprabu, K Shankar

Abstract read
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In one paragraph

Article in Journal of medical systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Data Integrity of Radiology Images Over an Insecure Network Using AES Technique.Asian Pacific journal of cancer prevention : APJCP · 2021
    Article
  4. Article
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.

T AvudaiappanDepartment of Computer Science and Engineering, K. Ramakrishnan College of Technology, Trichy, Tamilnadu, India.
R BalasubramanianDepartment of Computer Science and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu, India.
S Sundara PandiyanDepartment of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, Karnataka, India.
M SaravananDepartment of Information Technology, SRM Institute of Science and Technology, Kattankulathur, Tamilnadu, India.
S K LakshmanaprabuDepartment of Electronics and Instrumentation Engineering, B. S. Abdur Rahman Crescent Institute of Science and Technology, Chennai, Tamilnadu, India.
K ShankarSchool of Computing, Kalasalingam Academy of Research and Education, Krishnankoil, Tamilnadu, India. shankarcrypto@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Security is the most critical issue amid transmission of medical images because it contains sensitive information of patients. Medical image security is an essential method for secure the sensitive data when computerized images and their relevant patient data are transmitted across public networks. In this paper, the dual encryption procedure is utilized to encrypt the medical images. Initially Blowfish Encryption is considered and then signcryption algorithm is utilized to confirm the encryption model. After that, the Opposition based Flower Pollination (OFP) is utilized to upgrade the private and public keys. The performance of the proposed strategy is evaluated using performance measures such as Peak Signal to Noise Ratio (PSNR), entropy, Mean Square Error (MSE), and Correlation Coefficient (CC).

Indexed as

AlgorithmsComputer SecurityDiagnostic ImagingEntropyHumansSignal-To-Noise RatioBlowfish encryption algorithmMedical image securityPSNR and opposition based flower pollination optimizationSigncryption

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.