Quantitative analysis of digital images requires detection and segmentation of the borders of the object of interest. Accurate segmentation is required for volume determination, 3D rendering, radiation therapy, and su...Quantitative analysis of digital images requires detection and segmentation of the borders of the object of interest. Accurate segmentation is required for volume determination, 3D rendering, radiation therapy, and surgery planning. In medical images, segmentation has traditionally been done by human experts. Substantial computational and storage requirements become especially acute when object orientation and scale have to be considered. Therefore, automated or semi-automated segmentation techniques are essential if these software applications are ever to gain widespread clinical use. Many methods have been proposed to detect and segment 2D shapes, most of which involve template matching. Advanced segmentation techniques called Snakes or active contours have been used, considering deformable models or templates. The main purpose of this work is to apply segmentation techniques for the definition of 3D organs (anatomical structures) when big data information has been stored and must be organized by the doctors for medical diagnosis. The processes would be implemented in the CT images from patients with COVID-19.展开更多
【正】INTRODUCTION Anterior ciliary arteries provide 70%of the vascular supply of the anterior segment.A significant interruption of the vascular flow of these arteries increases the risk for anterior ischemia.Althoug...【正】INTRODUCTION Anterior ciliary arteries provide 70%of the vascular supply of the anterior segment.A significant interruption of the vascular flow of these arteries increases the risk for anterior ischemia.Although the frequency of this special condition is low after strabismus surgery(1:13 000)[1],its effects may involve substantial visual problems[2].We report the successful outcome of a new surgical approach for strabismus management in a case of high risk for anterior ischemia.Specifically,we show the correction of the horizontal ocular deviation by means of an adjustable muscle展开更多
文摘Quantitative analysis of digital images requires detection and segmentation of the borders of the object of interest. Accurate segmentation is required for volume determination, 3D rendering, radiation therapy, and surgery planning. In medical images, segmentation has traditionally been done by human experts. Substantial computational and storage requirements become especially acute when object orientation and scale have to be considered. Therefore, automated or semi-automated segmentation techniques are essential if these software applications are ever to gain widespread clinical use. Many methods have been proposed to detect and segment 2D shapes, most of which involve template matching. Advanced segmentation techniques called Snakes or active contours have been used, considering deformable models or templates. The main purpose of this work is to apply segmentation techniques for the definition of 3D organs (anatomical structures) when big data information has been stored and must be organized by the doctors for medical diagnosis. The processes would be implemented in the CT images from patients with COVID-19.
文摘【正】INTRODUCTION Anterior ciliary arteries provide 70%of the vascular supply of the anterior segment.A significant interruption of the vascular flow of these arteries increases the risk for anterior ischemia.Although the frequency of this special condition is low after strabismus surgery(1:13 000)[1],its effects may involve substantial visual problems[2].We report the successful outcome of a new surgical approach for strabismus management in a case of high risk for anterior ischemia.Specifically,we show the correction of the horizontal ocular deviation by means of an adjustable muscle
