Evidence map›Paper›PMID 34594397›Full record

ArticleComputational and mathematical methods in medicine2021

A Robust Image Encrypted Watermarking Technique for Neurodegenerative Disorder Diagnosis and Its Applications.

Chirag Sharma, Amandeep Bagga, Rajeev Sobti, Mohammad Shabaz, Rashid Amin

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Computational and mathematical methods in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.3field-weighted citation impact, top 18% of its field
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

5 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 3 countries.

Chirag SharmaDepartment of Computer Science and Engineering, Lovely Professional University, Punjab, India.ORCID https://orcid.org/0000-0002-6423-0230
Amandeep BaggaDepartment of Computer Application, Lovely Professional University, Punjab, India.ORCID https://orcid.org/0000-0002-1387-5928
Rajeev SobtiDepartment of Computer Science and Engineering, Lovely Professional University, Punjab, India.ORCID https://orcid.org/0000-0001-8636-7732
Mohammad ShabazArba Minch University, Ethiopia.ORCID https://orcid.org/0000-0001-5106-7609
Rashid AminDepartment of Computer Science, University of Engineering and Technology, Taxila, Pakistan.ORCID https://orcid.org/0000-0002-3143-689X
Lovely Professional University · INChandigarh University · INUniversity of Engineering and Technology Taxila · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of Internet technology has led to the availability of different multimedia data in various formats. The unapproved customers misuse multimedia information by conveying them on various web objections to acquire cash deceptively without the first copyright holder's intervention. Due to the rise in cases of COVID-19, lots of patient information are leaked without their knowledge, so an intelligent technique is required to protect the integrity of patient data by placing an invisible signal known as a watermark on the medical images. In this paper, a new method of watermarking is proposed on both standard and medical images. The paper addresses the use of digital rights management in medical field applications such as embedding the watermark in medical images related to neurodegenerative disorders, lung disorders, and heart issues. The various quality parameters are used to figure out the evaluation of the developed method. In addition, the testing of the watermarking scheme is done by applying various signal processing attacks.

Indexed as

Computer SecurityAlgorithmsComputational BiologyCOVID-19HumansImage Interpretation, Computer-AssistedInternetModels, StatisticalNeurodegenerative Diseases

Identifiers

PMID34594397
PMCPMC8478543
OpenAlexW3201570041

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.