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Knowledge--based enhancement of megavoltage images in radiation therapy using a hybrid neuro-fuzzy system

机译:基于知识的混合神经模糊系统增强放射治疗中的兆伏电压图像

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Megavoltage images (MVIs) are used in radiation therapy for verification of the patient's position during cancer treatment. Due to the physics of imaging devices, the quality of MVI is very poor. In this work, we propose a hybrid neuro-fuzzy system consisting of fuzzy techniques and neural nets for knowledge--based enhancement of MVIs. The fuzzy enhancement includes different contrast adaptation techniques and also soft filtering, respectively. A modified associative memory is trained using a priori knowledge for image restoration. In order to consider the subjective demands of physicians, an observer--dependent overall system for contrast adaptation is also proposed.
机译:兆伏图像(MVI)用于放射治疗,以验证癌症治疗期间患者的位置。由于成像设备的物理特性,MVI的质量非常差。在这项工作中,我们提出了一种混合神经模糊系统,该系统由模糊技术和神经网络组成,用于基于知识的MVI增强。模糊增强分别包括不同的对比度适应技术以及软滤波。使用用于图像恢复的先验知识来训练修改的关联存储器。为了考虑医师的主观要求,还提出了依赖于观察者的用于对比度适应的整体系统。

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