An agent-based approach for interpreting medical images

M. Popescu, Yi Shang
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Abstract

We present an agent-based approach for medical image interpretation. The system is based on the concept of active fusion for image recognition and is composed of two major types of intelligent agents: radiologist agents and patient representative agents. A patient representative agent takes images from the patient through a Web-based interface, asks for multiple opinions from radiologist agents in interpreting them, and then integrates the opinions for the user. A radiologist agent decomposes the image interpretation task into smaller subtasks, uses multiple agents to solve the subtasks, and combines the solutions to the subtasks intelligently to solve the image interpretation problem.
基于代理的医学图像解释方法
我们提出了一种基于智能体的医学图像解释方法。该系统基于图像识别的主动融合概念,由两大类智能代理组成:放射科医生代理和患者代表代理。患者代表代理通过基于web的界面从患者获取图像,在解释图像时询问放射科医生代理的多个意见,然后为用户整合这些意见。放射科代理将图像判读任务分解为更小的子任务,使用多个代理来解决子任务,并将子任务的解决方案智能地组合在一起来解决图像判读问题。
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