Image segmentation is a process that is intended to get the objects contained in the image by dividing the image into several regions that have similar attributes on the object. The main purpose of image segmentation is to facilitate the analysis process so the results more meaningful. Image segmentation is usually used to locate objects and boundaries in an image. In the medical world in particular, areas that have similar attributes often found in the image tissues or organs in humans was observed with medical devices such as organs and ultrasound scanning. In this study examined how image segmentation using fuzzy level set by utilizing the GPU via a platform called CUDA. The result is a developed image segmentation 141x able to a...
Fuzzy Connectedness is an important image segmenta-tion routine for image processing of medical imag...
Level-set methods are commonly used to segment regions of interest within images or volumes. These t...
Commodity graphics hardware has become a cost-effective parallel platform to solve many general comp...
The rapid development of computer technology has had a significant influence on advances in medical ...
Image segmentation techniques using fuzzy connectedness principles have shown their effectiveness in...
Image segmentation is an important process of image processing in the biomedical field. The method ...
Medical imaging techniques such as CT, MRI and x-ray imaging are a crucial component of modern diagn...
Image processing technology is now widely used in the health area, one example is to help the radiol...
The field of medical image analysis is becoming an increasingly important part of the medical profes...
Modern graphics processing units (GPUs) have evolved into high-performance processors with fully pro...
This paper presents a novel VLSI architecture for image segmentation. The architecture is based on t...
While level sets have demonstrated a great potential for 3D medical image segmentation, their useful...
Medical image are considered important in medical world. Medical image can be used for surgery prep...
While level sets have demonstrated a great potential for 3D medical image segmentation, their useful...
Intuitionistic fuzzy edge detection (IFED) algorithm has been used in the signification or character...
Fuzzy Connectedness is an important image segmenta-tion routine for image processing of medical imag...
Level-set methods are commonly used to segment regions of interest within images or volumes. These t...
Commodity graphics hardware has become a cost-effective parallel platform to solve many general comp...
The rapid development of computer technology has had a significant influence on advances in medical ...
Image segmentation techniques using fuzzy connectedness principles have shown their effectiveness in...
Image segmentation is an important process of image processing in the biomedical field. The method ...
Medical imaging techniques such as CT, MRI and x-ray imaging are a crucial component of modern diagn...
Image processing technology is now widely used in the health area, one example is to help the radiol...
The field of medical image analysis is becoming an increasingly important part of the medical profes...
Modern graphics processing units (GPUs) have evolved into high-performance processors with fully pro...
This paper presents a novel VLSI architecture for image segmentation. The architecture is based on t...
While level sets have demonstrated a great potential for 3D medical image segmentation, their useful...
Medical image are considered important in medical world. Medical image can be used for surgery prep...
While level sets have demonstrated a great potential for 3D medical image segmentation, their useful...
Intuitionistic fuzzy edge detection (IFED) algorithm has been used in the signification or character...
Fuzzy Connectedness is an important image segmenta-tion routine for image processing of medical imag...
Level-set methods are commonly used to segment regions of interest within images or volumes. These t...
Commodity graphics hardware has become a cost-effective parallel platform to solve many general comp...