Smoothing filters in synthetic cerebral magnetic resonance images: A comparative study

This paper presents the evaluation of two computational techniques for smoothing noise that might be present in synthetic images or numerical phantoms of magnetic resonance (MRI). The images that will serve as the databases (DB) during the course of this evaluation are available freely on the Internet and are reported in specialized literature as synthetic images called BrainWeb. The images that belong to this DB were contaminated with Rician noise, this being the most frequent type of noise in real MRI images. Also, the techniques that are usually considered to minimize the impact of Rician noise on the quality of BrainWeb images are matched with the Gaussian filter (GF) and an anisotropic diffusion filter, based on the gradient of the image (GADF). Each of these filters has 2 parameters that control their operation and, therefore, undergo a rigorous tuning process to identify the optimal values that guarantee the best performance of both the GF and the GADF. The peak of the signal-to-noise ratio (PSNR) and the computation time are considered as key elements to analyze the behavior of each of the filtering techniques applied. The results indicate that: a) both filters generate PSNR values comparable to each other. b) The GF requires a significantly shorter computation time to soften the Rician noise present in the considered DB. Keywords: Synthetic Cerebral images, Magnetic resonance, Rician noise, Gaussian filter, Anisotropic diffusion filter, PSNR.

• Autores: Gelvez Almeida, Elkin; Vera, Miguel Ángel; Huérfano Maldonado, Yoleidy Katherine; Valbuena Prada, Óscar; Salazar Echeverria, Williams Justo José; Vera Contreras, María Isabel; Borrero Rodríguez, Maryuri Astrid; Barrera Cortes, Doris Yaneth; Hernández Morantes, Carlos; Molina Mujica, Ángel Valentín; Martínez, Luis Javier; Sáenz Peña, Frank Hernando; ‪Vivas García, Marisela; Contreras Velásquez, Julio César; Restrepo Morales, Jorge Aníbal; Vanegas López, Juan Gabriel; Salazar Torres, Juan Pablo; Contreras Santander, Yudith Liliana
• Tipo de recurso: Article of investigation
• Fecha de publicación: 2018
• Institución: Tecnológico de Antioquia
• Repositorio: Repositorio Tdea
• Idioma: eng
• OAI Identifier: oai:dspace.tdea.edu.co:tdea/2845
• Acceso en línea: https://dspace.tdea.edu.co/handle/tdea/2845
• Palabra clave: Magnetic Resonance; Resonancia Magnética; Ressonância Magnética; Synthetic Cerebral images; Imágenes sintéticas cerebrales; Rician noise; Ruido Riciano; Gaussian filter; Filtro Gausiano; Anisotropic diffusion filter; Filtro de difusión anisotrópica; PSNR
• Rights: openAccess
• License: https://creativecommons.org/licenses/by-nd/4.0/