Add to ORKGAbstract—We compare the performance of hand-tuned CUDA implementations of bilateral and anisotropic dif-fusion filters for denoising 3D MRI datasets. Our tests sweep comparable parameters for the two filters and measure total runtime, memory bandwidth, computational throughput, and mean squared errors relative to a noiseless reference dataset. I
Nonlocal Means (NLM) algorithm is widely considered as a state-of-the-art denoising filter in many r...
This work analyzes the role of graphic processing units (GPUs) in the framework of traditional paral...
Abstract—Denoising is a crucial step to increase image conspicuity and to improve the performances o...
We compare the performance of hand-tuned CUDA implementations of bilateral and anisotropic diffusion...
This report explores using GPUs as a platform for performing high performance medical image data pro...
The raw computational power of GPU accelerators enables fast denoising of 3D MR images using bilater...
Real time medical image processing is necessary in the domain of remote medical care, diagnostics an...
Image smoothing is a fundamental operation in computer vision and image processing. This work has tw...
Over the past decade, computing architectures have continued to exploit multiple levels of paralleli...
Obtaining high quality images MR is desirable not only for accurate visual assessment but also faura...
Frequently MRI data is characterised by a relatively low signal to noise ratio (SNR) or contrast to ...
The quality of an image is highly critical for applications such as robotic vision, surveillance, me...
Smoothing and noise reduction of images is often an important first step in image processing applicat...
Frequently MRI data is characterised by a relatively low signal to noise ratio (SNR) or contrast to ...
The presented work deals with the efficient implementation of volumetric diffusion filters on modern...
Nonlocal Means (NLM) algorithm is widely considered as a state-of-the-art denoising filter in many r...
This work analyzes the role of graphic processing units (GPUs) in the framework of traditional paral...
Abstract—Denoising is a crucial step to increase image conspicuity and to improve the performances o...
We compare the performance of hand-tuned CUDA implementations of bilateral and anisotropic diffusion...
This report explores using GPUs as a platform for performing high performance medical image data pro...
The raw computational power of GPU accelerators enables fast denoising of 3D MR images using bilater...
Real time medical image processing is necessary in the domain of remote medical care, diagnostics an...
Image smoothing is a fundamental operation in computer vision and image processing. This work has tw...
Over the past decade, computing architectures have continued to exploit multiple levels of paralleli...
Obtaining high quality images MR is desirable not only for accurate visual assessment but also faura...
Frequently MRI data is characterised by a relatively low signal to noise ratio (SNR) or contrast to ...
The quality of an image is highly critical for applications such as robotic vision, surveillance, me...
Smoothing and noise reduction of images is often an important first step in image processing applicat...
Frequently MRI data is characterised by a relatively low signal to noise ratio (SNR) or contrast to ...
The presented work deals with the efficient implementation of volumetric diffusion filters on modern...
Nonlocal Means (NLM) algorithm is widely considered as a state-of-the-art denoising filter in many r...
This work analyzes the role of graphic processing units (GPUs) in the framework of traditional paral...
Abstract—Denoising is a crucial step to increase image conspicuity and to improve the performances o...