Evidence map›Paper›PMID 41951664›Full record

ArticleScientific reports2026

A geometric function theoretic approach to MRI distortion correction using Miller Ross Poisson series.

S Manoj, B Srutha Keerthi

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

S ManojDepartment of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Chennai, 600127, India.
B Srutha KeerthiDepartment of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Chennai, 600127, India. sruthakeerthi.b@vit.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study focuses on the newly introduced subclass of Sakaguchi-type function associated with the Miller–Ross-type Poisson distribution series. Using the proposed operator, we derive several coefficient bound, inverse function estimates, initial logarithmic coefficient results and Feketo-Szego type inequalities. Furthermore, growth, distortion, convex combination properties, subordination outcomes, and partial sum results are derived for the defined class. Application part demonstrates how the obtained coefficient bounds can be employed to design an analytic correction operator for improving the quality of distorted Magnetic Resonance Imaging (MRI) scans. Numerical experiments on real datasets validate the effectiveness of the proposed model, showing significant improvement in terms of MSE, PSNR, and SSIM. These results highlight the interplay between geometric function theory and practical imaging problems, thereby providing a new perspective on the use of analytic function subclasses in applied sciences.

Indexed as

Analytic functionsFekete-Szego inequalityGeometric properties.Miller-Ross distribution seriesStarlike functionSubordinationUnivalent function

Identifiers

PMID41951664
PMCPMC13061884

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