AIMC Topic: Spiral Cone-Beam Computed Tomography

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A preliminary study of using a deep convolution neural network to generate synthesized CT images based on CBCT for adaptive radiotherapy of nasopharyngeal carcinoma.

Physics in medicine and biology
This study aims to utilize a deep convolutional neural network (DCNN) for synthesized CT image generation based on cone-beam CT (CBCT) and to apply the images to dose calculations for nasopharyngeal carcinoma (NPC). An encoder-decoder 2D U-Net neural...

Performance of artificial intelligence using oral and maxillofacial CBCT images: A systematic review and meta-analysis.

Nigerian journal of clinical practice
BACKGROUND: Artificial intelligence (AI) has the potential to enhance health care efficiency and diagnostic accuracy.

Observations And Experiments For The Definition Of A New Robotic Device Dedicated To CT, CBCT And MRI-Guided Percutaneous Procedures.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this paper, we present the work achieved to define the robotic functionalities of interest for percutaneous procedures as performed in interventional radiology. Our contributions are twofold. First, a detailed task analysis is performed with workf...

Statistical Iterative CBCT Reconstruction Based on Neural Network.

IEEE transactions on medical imaging
Cone-beam computed tomography (CBCT) plays an important role in radiation therapy. Statistical iterative reconstruction (SIR) algorithms with specially designed penalty terms provide good performance for low-dose CBCT imaging. Among others, the total...