Objective: To propose a new method for effectively and rapidly removing the ring artifacts in CT images based on image post-processing.
Methods: The CT image with ring artifacts in the Cartesian coordinate was first transformed into an image with line artifacts in the polar coordinate. The image in the polar coordinate was then filtered by designing a one-dimensional filter to calculate the mean and variance of each pixel after filtering, which were compared with the variance threshold value and the pixel threshold value to determine the position of the artifacts for corrections accordingly. Finally, the polar coordinate image was converted into Cartesian coordinate image.
Results: Simulated and actual CT data experimental results demonstrated the efficiency of this method for removing artifacts, retaining the image fidelity and reducing the processing time.
Conclusion: The new method can accurately recognize the position of the artifacts and effectively remove them to facilitate the clinical diagnosis.
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JACC Cardiovasc Interv
January 2025
Department of Cardiology, Ehime Prefectural Imabari Hospital, Imabari, Japan.
Phys Med Biol
January 2025
Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Room 3209, CBIS/BME, 110 8th Street, Troy, NY 12180, USA, Troy, 12180, UNITED STATES.
We strive to overcome the challenges posed by ring artifacts in X-ray computed tomography (CT) by developing a novel approach for generating training data for deep learning-based methods. Training such networks require large, high quality, datasets that are often generated in the data domain, time-consuming and expensive. Our objective is to develop a technique for synthesizing realistic ring artifacts directly in the image domain, enabling scalable production of training data without relying on specific imaging system physics.
View Article and Find Full Text PDFAdv Radiat Oncol
February 2025
Department of Radiation Oncology, University of Utah, Salt Lake City, Utah.
Purpose: To evaluate the image quality of an ultrafast cone-beam computed tomography (CBCT) system-Varian HyperSight.
Methods And Materials: In this evaluation, 5 studies were performed to assess the image quality of HyperSight CBCT. First, a HyperSight CBCT image quality evaluation was performed and compared with Siemens simulation-CT and Varian TrueBeam CBCT.
Photoacoustics
February 2025
School of Information Engineering, Nanchang University, Nanchang 330031, China.
Photoacoustic tomography, a novel non-invasive imaging modality, combines the principles of optical and acoustic imaging for use in biomedical applications. In scenarios where photoacoustic signal acquisition is insufficient due to sparse-view sampling, conventional direct reconstruction methods significantly degrade image resolution and generate numerous artifacts. To mitigate these constraints, a novel sinogram-domain priors guided extremely sparse-view reconstruction method for photoacoustic tomography boosted by enhanced diffusion model is proposed.
View Article and Find Full Text PDFBiomed Phys Eng Express
December 2024
Division of Biomedical Engineering, College of Engineering, University of Saskatchewan, Saskatoon, SK S7N 5A9, Canada.
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