基于域变换滤波分段线性回归策略的高效医学图像超分辨率

IF 1.5 4区计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Concurrency and Computation-Practice & Experience Pub Date : 2025-02-18 DOI:10.1002/cpe.70016

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引用次数: 0

摘要

撤稿：D. C. Lepcha， B. Goyal， A. Dogra, s . h。Wang，“基于分段线性回归策略的高效医学图像超分辨率的域变换滤波”，并发与计算：实践与经验，第34期。20 (2022): e6644, https://doi.org/10.1002/cpe.6644.The上述文章于2021年10月4日在Wiley online Library （wileyonlinelibrary.com）上发表，经期刊编辑David W. Walker、Jinjun Chen、Nitin Auluck和Martin Berzins同意撤回；约翰·威利&；子有限公司由于发现同行评议和出版过程被操纵，因此已同意撤回。此外，对这篇手稿的详细调查显示，这篇手稿的部分内容显然是捏造的，因此这篇手稿的结论在很大程度上受到了损害。作者已被告知撤稿的决定。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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RETRACTION: An Efficient Medical Image Super Resolution Based on Piecewise Linear Regression Strategy Using Domain Transform Filtering

RETRACTION: D. C. Lepcha, B. Goyal, A. Dogra, and S.-H. Wang, “ An Efficient Medical Image Super Resolution Based on Piecewise Linear Regression Strategy Using Domain Transform Filtering,” Concurrency and Computation: Practice and Experience 34, no. 20 (2022): e6644, https://doi.org/10.1002/cpe.6644.

The above article, published online on 4 October 2021 in Wiley Online Library ( wileyonlinelibrary.com), has been retracted by agreement between the journal Editors, David W. Walker, Jinjun Chen, Nitin Auluck, and Martin Berzins; and John Wiley & Sons Ltd. The retraction has been agreed on as the peer review and publishing process was found to be manipulated. Furthermore, a detailed investigation of this manuscript revealed that parts of this manuscript are unambiguously fabricated, and so the conclusions of this manuscript are substantially compromised. The authors have been informed of the decision to retract.

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来源期刊

Concurrency and Computation-Practice & Experience 工程技术-计算机：理论方法

CiteScore

5.00

自引率

10.00%

发文量

664

审稿时长

9.6 months

期刊介绍： Concurrency and Computation: Practice and Experience (CCPE) publishes high-quality, original research papers, and authoritative research review papers, in the overlapping fields of: Parallel and distributed computing; High-performance computing; Computational and data science; Artificial intelligence and machine learning; Big data applications, algorithms, and systems; Network science; Ontologies and semantics; Security and privacy; Cloud/edge/fog computing; Green computing; and Quantum computing.