Description and Use of Three-Dimensional Numerical Phantoms of Cardiac Computed Tomography Images

Miguel Vera (), Antonio Bravo and Rubén Medina
Additional contact information
Miguel Vera: Facultad de Ciencias Básicas y Biomédicas, Universidad Simón Bolívar, Cúcuta 540004, Colombia
Antonio Bravo: Facultad de Ciencias Básicas y Biomédicas, Universidad Simón Bolívar, Cúcuta 540004, Colombia
Rubén Medina: CIBYTEL-Engineering School, Universidad de Los Andes, Núcleo La Hechicera, Mérida 5101, Venezuela

Data, 2022, vol. 7, issue 8, 1-10

Abstract: The World Health Organization indicates the top cause of death is heart disease. These diseases can be detected using several imaging modalities, especially cardiac computed tomography (CT), whose images have imperfections associated with noise and certain artifacts. To minimize the impact of these imperfections on the quality of the CT images, several researchers have developed digital image processing techniques (DPIT) by which the quality is evaluated considering several metrics and databases (DB), both real and simulated. This article describes the processes that made it possible to generate and utilize six three-dimensional synthetic cardiac DBs or voxels-based numerical phantoms. An exhaustive analysis of the most relevant features of images of the left ventricle, belonging to a real CT DB of the human heart, was performed. These features are recreated in the synthetic DBs, generating a reference phantom or ground truth free of imperfections (DB1) and five phantoms, in which Poisson noise (DB2), stair-step artifact (DB3), streak artifact (DB4), both artifacts (DB5) and all imperfections (DB6) are incorporated. These DBs can be used to determine the performance of DPIT, aimed at decreasing the effect of these imperfections on the quality of cardiac images.

Keywords: numerical phantoms; cardiac dataset; processing techniques; artifacts; Poisson noise (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2306-5729/7/8/115/pdf (application/pdf)
https://www.mdpi.com/2306-5729/7/8/115/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jdataj:v:7:y:2022:i:8:p:115-:d:889026

Access Statistics for this article

Data is currently edited by Ms. Cecilia Yang

More articles in Data from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().