BACKGROUND: Impacted canines are one of the most frequently encountered dental anomalies in maxillofacial practice. Accurate localization of these teeth is crucial for treatment planning, and Cone Beam Computed Tomography (CBCT) offers detailed 3D im...
Monochromatic cone beam computed tomography reconstruction algorithms are still most prominent in practice. Since the x-ray detectors of today's machines are mostly energy integrating detectors and thus not able to resolve photon energy levels, recon...
. Accurate dose accumulation relies on deformable image registration (DIR) to track dose across multiple images. However, DIR introduces uncertainties that can impact cumulative dose distributions. In this study, we present a probabilistic framework ...
Accurate dose calculation on cone beam computed tomography (CBCT) images is essential for modern proton treatment planning workflows, particularly when accounting for inter-fractional anatomical changes in adaptive treatment scenarios. Traditional CB...
BACKGROUND: To develop a deep learning-based model that is capable of automatically segmenting teeth in cone-beam computed tomography (CBCT) images and generating auxiliary diagnostic reports.
INTRODUCTION: This study aimed to validate an artificial intelligence (AI)-based automated image analysis for three-dimensional (3D) characterization of impacted canine position. In addition, it compared clinical treatment plans developed using conve...
BACKGROUND: This study compared the accuracy (defined by trueness and precision) of implant placement between a semi-autonomous robotic system (SARS) and a dynamic navigation system (DNS) in completely edentulous models, evaluating the influence of a...
BACKGROUND: The anatomical relationship between the maxillary sinus and maxillary molars is critical for planning dental procedures such as tooth extraction, implant placement and periodontal surgery.
OBJECTIVES: Current dental CBCT segmentation tools often lack accuracy, accessibility, or comprehensive anatomical coverage. To address this, we constructed a densely annotated dental CBCT dataset and developed a deep learning model, OraSeg, for toot...
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Sep 25, 2025
This paper examines the current challenges in computed tomography (CT), with a critical exploration of existing methodologies from a mathematical perspective. Specifically, it aims to identify research directions to enhance image quality in low-dose,...
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