Automated Registration of Freehand B-Mode Ultrasound and Magnetic Resonance Imaging of the Carotid Arteries Based on Geometric Features

Digital image filters are not necessarily related to improvement in diagnostic of degenerative bone changes in the temporomandibular joint on cone beam computed tomography

“…Digital filters for image enhancement are an alternative approach used to improve images, thus facilitating the evaluation of temporomandibular joint (TMJ) changes, in which specific software allows several valuable image manipulations for soft or bony tissues. The application of these filters can strongly influence the image quality depending on the type of filter used, as one can reduce artifacts, reduce image noise, soften gray tones and detect and increase edges (Carvalho et al, 2017;Eliášová & Dostálová, 2017).…”

“…The use of digital filters can improve images of poor quality as a result of artifacts, metallic restorations or high noise levels at low radiation dose as well as the detection of large amounts of diffused radiation. Other factors such as voxel size, tension peak, milliamperage, exposure time, FOV size, and rotation degree are also involved (Carvalho et al, 2017;García-Sanz et al, 2017) filters minimize the image noise by using mathematical algorithms in order to reduce or increase a specific characteristic (Eliášová & Dostálová, 2017;Soares et al, 2021;Verner et al, 2017).…”

“…There are a few studies (Carvalho et al, 2017;De Sousa et al, 2017;Eliášová & Dostálová, 2017; García-Sanz et al, Research, Society and Development, v. 10, n. 4, e44010414296, 2021 (CC BY 4.0) | ISSN 2525-3409 | DOI: http://dx.doi.org/10.33448/rsd-v10i4.14296 3 2017) assessing the influence of filters on the quality of images and on the diagnostic capacity for condyle changes. Therefore, the present work aimed to study the influence of digital filters on the diagnostic of degenerative bone changes in the TMJ.…”

Cooperative carotid artery centerline extraction in MRI

“…The main reason to extract the carotid artery centerline is to define a ROI for further processing such as registration [ 4 ], or to initialize a segmentation method [ 1 – 3 ], where reducing the centerline failures is very important. If the centerlines follow a wrong path outside the vessel, a registration or segmentation will likely fail [ 2 , 5 ]. Therefore, we think the presented method to extract the centerlines is highly suitable for further processing, as it considerably reduces the number of failures.…”

“…Centerline detection of the carotid artery in MRI is important to analyze its geometry [ 1 ], and to provide input for segmentation [ 1 – 3 ] and registration methods of the carotid artery [ 4 , 5 ].…”