评估一个深度学习系统自动计算笔划方面得分

Su-min Jung, T. Whangbo
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引用次数: 5

摘要

中风是世界上导致死亡的主要原因之一。这是一种会导致永久残疾的危险疾病。CT和MRI是诊断脑卒中的代表性影像学诊断工具。特别是,CT具有快速检查疾病的优势。阿尔伯塔中风项目早期CT评分(ASPECTS)被广泛用作基于CT图像显示中风严重程度的工具。然而,它在医学专家中存在评分差异问题。为了解决这一问题,本研究提出了一种基于图像处理和深度学习技术的对象和自动ASPECT评分估计系统。
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Evaluating a Deep-Learning System for Automatically Calculating the Stroke ASPECT Score
The stroke is one of the leading causes of death around the world. It is a dangerous disease that results in a permanent disability. CT and MRI are representative imaging diagnostic tools for diagnosing the stroke. Particularly, CT has an advantage of examining the disease quickly. The Alberta Stroke Program Early CT Score (ASPECTS) is widely used as a tool to demonstrate the severity of the stroke based on CT images. However, it has a scoring variability issue among medical experts. This study proposed an object and automated ASPECT Score estimation system based on the image processing and deep learning technology for resolving the issue.
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