نتایج جستجو برای: retinal image segmentation
تعداد نتایج: 489466 فیلتر نتایج به سال:
introduction this research addresses the automatic extraction of alluvial fans using four methods of segmentation from satellite data. this segmentation method divides images into partitions. it is typically used to recognize objects or other relevant purposes in digital images (fu, 2013:3260). alluvial fans have always been a landform that attracts human because they are suitable areas for liv...
Spectral domain optical coherence tomography (SD-OCT) is used for cross-section imaging, in ophthalmology for retinal tissue. Extracting structural information about the retinal layers is becoming increasingly important, as this has the potential to expand retinal disease research and improve diagnosis. The purpose of our study was to facilitate a robust and efficient algorithm for segmentation...
The separation of the retinal vessel network into distinct arterial and venous vessel trees is of high interest. We propose an automated method for identification and separation of retinal vessel trees in a retinal color image by converting a vessel segmentation image into a vessel segment map and identifying the individual vessel trees by graph search. Orientation, width, and intensity of each...
The appearance and structure of blood vessels in retinal images have an important role in diagnosis of diseases. This paper proposes a method for automatic retinal vessel segmentation. In this work, a novel preprocessing based on local histogram equalization is used to enhance the original image then pixels are classified as vessel and nonvessel using a classifier. For this classification, spec...
Spectral domain optical coherence tomography (SD-OCT) is a useful tool for the visualization of drusen, a retinal abnormality seen in patients with age-related macular degeneration (AMD); however, objective assessment of drusen is thwarted by the lack of a method to robustly quantify these lesions on serial OCT images. Here, we describe an automatic drusen segmentation method for SD-OCT retinal...
Retinal blood vessels segmentation plays an important role for retinal image analysis. In this paper, we propose robust retinal blood vessel segmentation method based on reinforcement local descriptions. A novel line set based feature is firstly developed to capture local shape information of vessels by employing the length prior of vessels, which is robust to intensity variety. After that, loc...
This paper presents a new supervised method for segmentation of blood vessels in retinal images. This method uses an ensemble system of boot strapped decision trees and utilizes a feature vector based on the orientation analysis of gradient vector field, morphological linear transformation, line strength measures and Gabor filter responses. The feature vector encodes information to handle the h...
Retinal and intra-retinal layer thicknesses are routinely generated from optical coherence tomography (OCT) images, but on-board software capabilities and image scaling assumptions are not consistent across devices. This study evaluates the device-independent Iowa Reference Algorithms (Iowa Institute for Biomedical Imaging) for automated intra-retinal layer segmentation and image scaling for th...
Blood vessel in retinal image plays a vital role in medical diagnosis of many diseases. Diabetic retinopathy is one of the diseases which damages the retina and leads to blindness. Segmentation of blood vessels is helpful for ophthalmologists and this paper presents a new automatic method to extract blood vessels with high accuracy. This algorithm is comprised of optimized Gabor filter with loc...
introduction: nowadays virtual colonoscopy has become a reliable and efficient method of detecting primary stages of colon cancer such as polyp detection. one of the most important and crucial stages of virtual colonoscopy is colon segmentation because an incorrect segmentation may lead to a misdiagnosis. materials and methods: in this work, a hybrid method based on geometric deformable models...
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