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Retinal vessel segmentation is an important step for the detection of numerous system diseases, such as glaucoma, diabetic retinopathy, and others. Thus, the retinal blood vessel analysis can be used to diagnose and to monitor the progress of these diseases. Manual segmentation of fundus images is a long and tedious task that requires a specialist. Therefore, many algorithms have been developed for...
The medical imaging analysis is the process to view and understand the internal structure and function of the physiological system in medical diagnostic and therapeutic applications. Coronary artery angiography is playing a decisive role to determine the presence of cardiac diseases and the consequences for a therapeutic approach. So, the coronary angiography is remained for determining the extent,...
In this paper we have presented an algorithm for vessel detection in retinal color images which works based on local Radon transform and morphological reconstruction. In our previous work, the algorithm was applied to conjunctival images and the performance was evaluated subjectively. In this work an extended version of the algorithm is applied to retinal images and our aim is to detect vessels in...
Attribute filters allow enhancement and extraction of features without distorting their borders, and never introduce new image features. These are highly desirable properties in biomedical imaging, where accurate shape analysis is paramount. However, setting the attribute-threshold parameters has to date only been done manually. This paper explores simple, fast and automated methods of computing attribute...
Exudates are one of the earliest and most prevalent symptoms of diseases leading to blindness such as diabetic retinopathy and wet macular degeneration. Certain areas of the retina with such conditions are to be photocoagulated by laser to stop the disease progress and prevent blindness. Outlining these areas is dependent on outlining the exudates, the blood vessels, the optic disc and the macula...
In this paper, an algorithm is developed for anatomical structures segmentation based on CT head images. The segmented structure can be used for image guide surgery navigations. In our method, intensity rescaling, the threshold algorithm, region growing method, fast-marching method (FMM) and mathematical morphology are combined and used systematically. Due to the low contrast of the CT images, intensity...
In image processing, segmentation is considered one of the most important and hardest operations. The media-adventitia segmentation, in Intravascular Ultrasound (IVUS) images, is one of the first steps for a vase 3D reconstruction, and it is an important operation for many applications: measurements of its border circumference, area and radius; for studies about the mechanical properties and anatomical...
Medical images edge detection is one of the most important pre-processing steps in medical image segmentation and 3D reconstruction. In this paper, an edge detection algorithm using an uninorm-based fuzzy morphology is proposed. It is shown that this algorithm is robust when it is applied to different types of noisy images. It improves the results of other well-known algorithms including classical...
The segmentation of pathological interesting region is the key point in medical image segmentation, because the interesting regions include important diagnostic information. This paper proposed a new segmentation method that is based on the order morphological gradient map and the improved region growing arithmetic. The order morphological gradient map can be obtained by the order morphological transformation...
This paper presents a user steered segmentation algorithm based on the radial basis function (RBF) curve fitting for blurred medical image caused by the continuity of organism, which results in the difficulties of algorithm based on the radial basis function (RBF) curve fitting for blurred medical image caused by the continuity of organism, which results in the difficulties of satisfactory automatic...
In this paper, a novel approach for vessels extraction edge-based image segmentation is proposed. Vessels segmentation and extraction play an important role in supporting computer assistance for diagnosis of Diabetic Retinopathy (DR). Diabetic Retinopathy is a severe and widely spread eye disease. The algorithms to detect and extract vessels from retinal images are mainly based on morphological filtering...
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