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dc.contributor.authorOzkul, Mine Cuneyitoglu
dc.contributor.authorMumcuoglu, Unal Erkan
dc.contributor.authorSancak, İbrahim Tanzer
dc.date.accessioned2019-12-30T07:24:32Z
dc.date.available2019-12-30T07:24:32Z
dc.date.issued2019
dc.identifier.citationCüneyitoğlu Özkul, M., Mumcuoğlu, Ü. E., & Sancak, İ. T. (2019). Single-image Bayesian Restoration and Multi-image Super-resolution Restoration for B-mode Ultrasound Using an Accurate System Model Involving Correlated Nature of the Speckle Noise. Ultrasonic imaging, 0161734619865961.en_US
dc.identifier.issn0161-7346
dc.identifier.urihttps://journals.sagepub.com/doi/full/10.1177/0161734619865961?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%3dpubmed
dc.identifier.urihttp://hdl.handle.net/20.500.11851/3229
dc.description.abstractB-mode ultrasound is an essential part of radiological examinations due to its low cost, safety, and portability, but has the drawbacks of the speckle noise and output of most systems is two-dimensional (2D) cross sections. Image restoration techniques, using mathematical models for image degradation and noise, can be used to boost resolution (deconvolution) as well as to reduce the speckle. In this study, new single-image Bayesian restoration (BR) and multi-image super-resolution restoration (BSRR) methods are proposed for in-plane B-mode ultrasound images. The spatially correlated nature of the speckle was modeled, allowing for examination of two different models for BR and BSRR for uncorrelated Gaussian (BR-UG, BSRR-UG) and correlated Gaussian (BR-CG, BSRR-CG). The performances of these models were compared with common image restoration methods (Wiener filter, bilateral filtering, and anisotropic diffusion). Well-recognized metrics (peak signal-to-noise ratio, contrast-to-noise ratio, and normalized information density) were used for algorithm free-parameter estimation and objective evaluations. The methods were tested using superficial tissue (2D scan data collected from volunteers, tissue-mimicking resolutions, and breast phantoms). Improvement in image quality was assessed by experts using visual grading analysis. In general, BSRR-CG performed better than all other methods. A potential downside of BSRR-CG is increased computation time, which can be addressed by the use of high-performance graphics processing units (GPUs).en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [2211-C]tr_TR
dc.language.isoengen_US
dc.publisherSAGE PUBLICATIONS INCen_US
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectimage restorationen_US
dc.subjectdeconvolutionen_US
dc.subjectsuper-resolutionen_US
dc.subjectspeckle reductionen_US
dc.subjectcorrelated noiseen_US
dc.subjectBayesianen_US
dc.titleSingle-image Bayesian Restoration and Multi-image Super-resolution Restoration for B-mode Ultrasound Using an Accurate System Model Involving Correlated Nature of the Speckle Noiseen_US
dc.typearticleen_US
dc.relation.journalUltrasonic Imagingen_US
dc.contributor.departmentTOBB ETÜ, Tıp Fakültesi, Dahili Tıp Bilimleri Bölümütr_TR
dc.contributor.departmentTOBB ETU, Faculty of Medicine, Department of Internal Medical Sciencesen_US
dc.identifier.volume41
dc.identifier.issue6
dc.identifier.startpage368
dc.identifier.endpage386
dc.identifier.wosWOS:000479949500001
dc.contributor.tobbetuauthorSancak, İbrahim Tanzer
dc.contributor.YOKid179834
dc.identifier.doi10.1177/0161734619865961
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıtr_TR


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