The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
As a classic image segmentation method, watershed algorithm is widely used. But the over-segmentation and sensitivity to noise are its drawbacks, many improved watershed methods have been developed to solve these problems. This paper presented an improved watershed algorithm for medical image segmentation. Firstly, an iterative data-adaptive Gaussian smoother is used to smooth large scale details...
Patient-specific correlation of perfusion defects and coronary arteries responsible for blood supply in the affected territories has the potential to improve accuracy of diagnosis and intervention planning, but cardiac cycle phase difference between perfusion and angiography datasets precludes the use of standard methods of 2D/3D registration. This paper presents a work-flow for mediated spatiotemporal...
The paper describes a set of approaches and routines designed to improve results in CT based 3D subtractive angiography of lower extremities via better global locally defined image data registration. Starting from the generic concept of 3D disparity-based flexible registration, modifications of this idea are made founded on prior anatomical knowledge, as segmentation into individual bone areas, their...
Automatic cell segmentation in phase contrast microscopy images play a very important role in the study the behavior of lymphocytes, such as cell motility, cell deformation, and cell population dynamics etc. In this paper, we have developed a set of algorithms for the microscopy image cell segmentation, in which three pairs of edge detection (Sobel, Prewitt and Laplace) based cell segmentation algorithms...
The histological grading of Hepatocellular Carcinoma is essential to prognosis and treatment planning. Providing a quantitative analysis by machine vision is desired for a determination of the grading result. However, the cells on the biopsy are not all in the some depth of focus under the microscope. Some cells in the images captured by machine may become a blur with a small variance of focus. These...
In the medical image processing different sources of images are providing complementary information so fusion of different source images will give more details for diagnosis of patients. In this paper an automatic region based image fusion algorithm is proposed which is applied on the registered Magnetic Resonance (MR) image of human brain. The aim of this paper is to detect all the information required...
Automatic cell segmentation and tracking in optical microscope images plays a very important role in the study the behaviour of lymphocytes. The variable image contrasts, and especially variable cell densities are major factors to affect the successful cell detection rates. In this paper, two inner and outer cell contours edge detection based cell segmentation algorithms are proposed and used in parallel...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.