GPU-based high-performance computing for radiation therapy
Recent developments in radiotherapy therapy demand high computation powers to solve
challenging problems in a timely fashion in a clinical environment. The graphics processing …
challenging problems in a timely fashion in a clinical environment. The graphics processing …
Applications of nonlocal means algorithm in low‐dose X‐ray CT image processing and reconstruction: a review
Low‐dose X‐ray computed tomography (LDCT) imaging is highly recommended for use in
the clinic because of growing concerns over excessive radiation exposure. However, the CT …
the clinic because of growing concerns over excessive radiation exposure. However, the CT …
CONRAD—A software framework for cone‐beam imaging in radiology
Purpose: In the community of x‐ray imaging, there is a multitude of tools and applications
that are used in scientific practice. Many of these tools are proprietary and can only be used …
that are used in scientific practice. Many of these tools are proprietary and can only be used …
Low-dose x-ray tomography through a deep convolutional neural network
Synchrotron-based X-ray tomography offers the potential for rapid large-scale
reconstructions of the interiors of materials and biological tissue at fine resolution. However …
reconstructions of the interiors of materials and biological tissue at fine resolution. However …
Ultralow‐parameter denoising: trainable bilateral filter layers in computed tomography
Background Computed tomography (CT) is widely used as an imaging tool to visualize three‐
dimensional structures with expressive bone‐soft tissue contrast. However, CT resolution …
dimensional structures with expressive bone‐soft tissue contrast. However, CT resolution …
Adaptive iterative reconstruction based on relative total variation for low-intensity computed tomography
C Gong, L Zeng - Signal Processing, 2019 - Elsevier
Low-intensity projections (high-level noise) may degrade computed tomography (CT) image
quality in some applications. CT image reconstruction from projections with low intensity has …
quality in some applications. CT image reconstruction from projections with low intensity has …
Trainable joint bilateral filters for enhanced prediction stability in low-dose CT
Low-dose computed tomography (CT) denoising algorithms aim to enable reduced patient
dose in routine CT acquisitions while maintaining high image quality. Recently, deep …
dose in routine CT acquisitions while maintaining high image quality. Recently, deep …
X-ray Imaging
In this chapter, the physical principles of X-rays are introduced. We start with a general
definition of X-rays compared to other well known rays, eg, the visible light. In Sec. 7.2, we …
definition of X-rays compared to other well known rays, eg, the visible light. In Sec. 7.2, we …
Comparison of CT noise reduction performances with deep learning-based, conventional, and combined denoising algorithms
ZA Balogh, BJ Kis - Medical Engineering & Physics, 2022 - Elsevier
Conventional noise reduction algorithms have been used in image processing for a very
long time, but recently, deep learning-based algorithms have been shown to significantly …
long time, but recently, deep learning-based algorithms have been shown to significantly …
Limited parameter denoising for low‐dose X‐ray computed tomography using deep reinforcement learning
Background The use of deep learning has successfully solved several problems in the field
of medical imaging. Deep learning has been applied to the CT denoising problem …
of medical imaging. Deep learning has been applied to the CT denoising problem …