AIMC Topic: Cone-Beam Computed Tomography

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The preliminary in vitro study and application of deep learning algorithm in cone beam computed tomography image implant recognition.

Scientific reports
To properly repair and maintain implants, which are bone tissue implants that replace natural tooth roots, it is crucial to accurately identify their brand and specification. Deep learning has demonstrated outstanding capabilities in analysis, such a...

Evaluation of deep learning for detecting intraosseous jaw lesions in cone beam computed tomography volumes.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: The study aim was to develop and assess the performance of a deep learning (DL) algorithm in the detection of radiolucent intraosseous jaw lesions in cone beam computed tomography (CBCT) volumes.

Technical note: Evaluation of deep learning based synthetic CTs clinical readiness for dose and NTCP driven head and neck adaptive proton therapy.

Medical physics
BACKGROUND: Adaptive proton therapy workflows rely on accurate imaging throughout the treatment course. Our centre currently utilizes weekly repeat CTs (rCTs) for treatment monitoring and plan adaptations. However, deep learning-based methods have re...

Volumetric tumor tracking from a single cone-beam X-ray projection image enabled by deep learning.

Medical image analysis
Radiotherapy serves as a pivotal treatment modality for malignant tumors. However, the accuracy of radiotherapy is significantly compromised due to respiratory-induced fluctuations in the size, shape, and position of the tumor. To address this challe...

Gradient-based geometry learning for fan-beam CT reconstruction.

Physics in medicine and biology
Incorporating computed tomography (CT) reconstruction operators into differentiable pipelines has proven beneficial in many applications. Such approaches usually focus on the projection data and keep the acquisition geometry fixed. However, precise k...

An artificial intelligence model for the radiographic diagnosis of osteoarthritis of the temporomandibular joint.

Scientific reports
The interpretation of the signs of Temporomandibular joint (TMJ) osteoarthritis on cone-beam computed tomography (CBCT) is highly subjective that hinders the diagnostic process. The objectives of this study were to develop and test the performance of...

Autologous Transplantation Tooth Guide Design Based on Deep Learning.

Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons
BACKGROUND: Autologous tooth transplantation requires precise surgical guide design, involving manual tracing of donor tooth contours based on patient cone-beam computed tomography (CBCT) scans. While manual corrections are time-consuming and prone t...

Image quality improvement in bowtie-filter-equipped cone-beam CT using a dual-domain neural network.

Medical physics
BACKGROUND: The bowtie-filter in cone-beam CT (CBCT) causes spatially nonuniform x-ray beam often leading to eclipse artifacts in the reconstructed image. The artifacts are further confounded by the patient scatter, which is therefore patient-depende...