In diagnosing diseases and planning surgeries the structure and length of blood vessels is of great importance. In this research we develop a novel method for the segmentation of 2-D and 3-D images with an application to blood vessel length measurements in 3-D abdominal MRI images. Our approach is robust to noise and does not require contrast enhanced images for segmentation. We use an effective algorithm for skeletonization, graph construction and shortest path estimation to measure the length of blood vessels of interest
Skeletonization is an iterative process frequently used in image processing to reduce the pictorial ...
This paper presents a method for three-dimensional (3D) segmentation of blood vessels, using a combi...
AbstractThis paper presents a reconstruction process to build the three-dimensional structure of cer...
In diagnosing diseases and planning surgeries the structure and length of blood vessels is of great ...
The aim of this paper is to introduce a method of blood-vessel tree segmentation in 3D volume and th...
Image segmentation is the problem of partitioning an image into meaningful parts, often consisting o...
Segmenting cerebral blood vessels is of great importance in diagnostic and clinical applications, es...
Medical imaging is nowadays much more than only providing data for diagnosis. It also links 'classic...
International audienceWe designed a generic method for segmenting the aneurismal sac of an abdominal...
The article discusses the design of appropriate methodology of segmentation and visualization of MRI...
Blood vessel segmentation plays a fundamental role in many computer-aided diagnosis (CAD) systems, s...
Medical imaging is an important part of the clinical workflow. With the increasing amount and comple...
The examination of abdominal aorta is an effective way to diagnose many cardiovascular diseases. Aor...
Micro-tomography produces high resolution images of biological structures such as vascular networks....
This thesis deals with the design, implementation and testing of an algorithm for segmentation of ce...
Skeletonization is an iterative process frequently used in image processing to reduce the pictorial ...
This paper presents a method for three-dimensional (3D) segmentation of blood vessels, using a combi...
AbstractThis paper presents a reconstruction process to build the three-dimensional structure of cer...
In diagnosing diseases and planning surgeries the structure and length of blood vessels is of great ...
The aim of this paper is to introduce a method of blood-vessel tree segmentation in 3D volume and th...
Image segmentation is the problem of partitioning an image into meaningful parts, often consisting o...
Segmenting cerebral blood vessels is of great importance in diagnostic and clinical applications, es...
Medical imaging is nowadays much more than only providing data for diagnosis. It also links 'classic...
International audienceWe designed a generic method for segmenting the aneurismal sac of an abdominal...
The article discusses the design of appropriate methodology of segmentation and visualization of MRI...
Blood vessel segmentation plays a fundamental role in many computer-aided diagnosis (CAD) systems, s...
Medical imaging is an important part of the clinical workflow. With the increasing amount and comple...
The examination of abdominal aorta is an effective way to diagnose many cardiovascular diseases. Aor...
Micro-tomography produces high resolution images of biological structures such as vascular networks....
This thesis deals with the design, implementation and testing of an algorithm for segmentation of ce...
Skeletonization is an iterative process frequently used in image processing to reduce the pictorial ...
This paper presents a method for three-dimensional (3D) segmentation of blood vessels, using a combi...
AbstractThis paper presents a reconstruction process to build the three-dimensional structure of cer...