Radon inversion via deep learning
The Radon transform is widely used in physical and life sciences, and one of its major
applications is in medical X-ray computed tomography (CT), which is significantly important …
applications is in medical X-ray computed tomography (CT), which is significantly important …
Artificial intelligence in radiotherapy: a technological review
K Sheng - Frontiers of Medicine, 2020 - Springer
Radiation therapy (RT) is widely used to treat cancer. Technological advances in RT have
occurred in the past 30 years. These advances, such as three-dimensional image guidance …
occurred in the past 30 years. These advances, such as three-dimensional image guidance …
Exact decomposition of joint low rankness and local smoothness plus sparse matrices
It is known that the decomposition in low-rank and sparse matrices (L+ S for short) can be
achieved by several Robust PCA techniques. Besides the low rankness, the local …
achieved by several Robust PCA techniques. Besides the low rankness, the local …
Automatic segmentation of the mandible from computed tomography scans for 3D virtual surgical planning using the convolutional neural network
B Qiu, J Guo, J Kraeima, HH Glas… - Physics in Medicine …, 2019 - iopscience.iop.org
Segmentation of mandibular bone in CT scans is crucial for 3D virtual surgical planning of
craniofacial tumor resection and free flap reconstruction of the resection defect, in order to …
craniofacial tumor resection and free flap reconstruction of the resection defect, in order to …
Self-supervised dynamic CT perfusion image denoising with deep neural networks
Dynamic computed tomography perfusion (CTP) imaging is a promising approach for acute
ischemic stroke diagnosis and evaluation. Hemodynamic parametric maps of cerebral …
ischemic stroke diagnosis and evaluation. Hemodynamic parametric maps of cerebral …
Generalized deep iterative reconstruction for sparse-view CT imaging
Sparse-view CT is a promising approach for reducing the x-ray radiation dose in clinical CT
imaging. However, the CT images reconstructed from the conventional filtered …
imaging. However, the CT images reconstructed from the conventional filtered …
Reconstruction of optical coherence tomography images using mixed low rank approximation and second order tensor based total variation method
PG Daneshmand, A Mehridehnavi… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This paper proposes a mixed low-rank approximation and second-order tensor-based total
variation (LRSOTTV) approach for the super-resolution and denoising of retinal optical …
variation (LRSOTTV) approach for the super-resolution and denoising of retinal optical …
Basis and current state of computed tomography perfusion imaging: a review
D Zeng, C Zeng, Z Zeng, S Li, Z Deng… - Physics in Medicine …, 2022 - iopscience.iop.org
Computed tomography perfusion (CTP) is a functional imaging that allows for providing
capillary-level hemodynamics information of the desired tissue in clinics. In this paper, we …
capillary-level hemodynamics information of the desired tissue in clinics. In this paper, we …
FONT-SIR: Fourth-order nonlocal tensor decomposition model for spectral CT image reconstruction
X Chen, W **a, Y Liu, H Chen, J Zhou… - … on Medical Imaging, 2022 - ieeexplore.ieee.org
Spectral computed tomography (CT) reconstructs images from different spectral data
through photon counting detectors (PCDs). However, due to the limited number of photons …
through photon counting detectors (PCDs). However, due to the limited number of photons …
SOUL-net: A sparse and low-rank unrolling network for spectral CT image reconstruction
Spectral computed tomography (CT) is an emerging technology, that generates a
multienergy attenuation map for the interior of an object and extends the traditional image …
multienergy attenuation map for the interior of an object and extends the traditional image …