Motion estimation and correction in SPECT, PET and CT
Patient motion impacts single photon emission computed tomography (SPECT), positron
emission tomography (PET) and x-ray computed tomography (CT) by giving rise to …
emission tomography (PET) and x-ray computed tomography (CT) by giving rise to …
Artificial intelligence for image registration in radiation oncology
Automatic image registration plays an important role in many aspects of the radiation
oncology workflow ranging from treatment simulation, image guided and adaptive …
oncology workflow ranging from treatment simulation, image guided and adaptive …
A series-based deep learning approach to lung nodule image classification
Simple Summary Medical image classification is an important task in computer-aided
diagnosis, medical image acquisition, and mining. Although deep learning has been shown …
diagnosis, medical image acquisition, and mining. Although deep learning has been shown …
Artifact Reduction in 3D and 4D Cone-beam Computed Tomography Images with Deep Learning-A Review
M Amirian, D Barco, I Herzig, FP Schilling - Ieee Access, 2024 - ieeexplore.ieee.org
Deep learning based approaches have been used to improve image quality in cone-beam
computed tomography (CBCT), a medical imaging technique often used in applications such …
computed tomography (CBCT), a medical imaging technique often used in applications such …
Deep learning‐based motion compensation for four‐dimensional cone‐beam computed tomography (4D‐CBCT) reconstruction
Abstract Background Motion‐compensated (MoCo) reconstruction shows great promise in
improving four‐dimensional cone‐beam computed tomography (4D‐CBCT) image quality …
improving four‐dimensional cone‐beam computed tomography (4D‐CBCT) image quality …
A review on 4D cone‐beam CT (4D‐CBCT) in radiation therapy: Technical advances and clinical applications
Cone‐beam CT (CBCT) is the most commonly used onboard imaging technique for target
localization in radiation therapy. Conventional 3D CBCT acquires x‐ray cone‐beam …
localization in radiation therapy. Conventional 3D CBCT acquires x‐ray cone‐beam …
PRIOR: Prior-regularized iterative optimization reconstruction for 4D CBCT
4D cone-beam computed tomography (CBCT) is an important imaging modality in image-
guided radiation therapy to address the motion-induced artifacts caused by organ …
guided radiation therapy to address the motion-induced artifacts caused by organ …
Dynamic cone-beam CT reconstruction using spatial and temporal implicit neural representation learning (STINR)
Objective. Dynamic cone-beam CT (CBCT) imaging is highly desired in image-guided
radiation therapy to provide volumetric images with high spatial and temporal resolutions to …
radiation therapy to provide volumetric images with high spatial and temporal resolutions to …
4D-AirNet: a temporally-resolved CBCT slice reconstruction method synergizing analytical and iterative method with deep learning
Abstract Four-dimensional (4D) cone-beam CT (CBCT) reconstructs temporally-resolved
phases of 3D volumes often with the same amount of projection data that are meant for …
phases of 3D volumes often with the same amount of projection data that are meant for …
Deep learning‐based synthetization of real‐time in‐treatment 4D images using surface motion and pretreatment images: A proof‐of‐concept study
Purpose To develop a deep learning model that maps body surface motion to internal
anatomy deformation, which is potentially applicable to dose‐free real‐time 4D virtual image …
anatomy deformation, which is potentially applicable to dose‐free real‐time 4D virtual image …