医学中的神经网络

R. Logeswaran
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引用次数: 10

摘要

自动检测肝脏胆管中的肿瘤是非常困难的,因为在使用磁共振胆管造影(MRCP)的事实上的非侵入性诊断图像中,肿瘤并不清楚可见。专家利用他们在解剖学上的经验,通过图像中没有预期的结构来诊断肿瘤。当然,对一个自动化系统来说,进行这样的诊断是非常困难的。本章提出了一种基于人工诊断原理以及自然图像处理技术和人工神经网络(ANN)相结合的算法,以协助对影响肝脏胆管的肿瘤进行初步诊断。结果显示,使用多层感知器(MLP)架构的人工神经网络开发的系统在执行困难的肿瘤自动初步检测方面的成功率超过88%,即使在存在其他胆道疾病的鲁棒临床测试图像中也是如此。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural Networks in Medicine
Automatic detection of tumours in the bile ducts of the liver is very difficult as often, in the de-facto non-invasive diagnostic images using magnetic resonance cholangiopancreatography (MRCP), tumours are not clearly visible. Specialists use their experience in anatomy to diagnose a tumour by absence of expected structures in the images. Naturally, undertaking such diagnosis is very difficult for an automated system. This chapter proposes an algorithm that is based on a combination of the manual diagnosis principles along with nature-inspired image processing techniques and artificial neural networks (ANN) to assist in the preliminary diagnosis of tumours affecting the bile ducts in the liver. The results obtained show over 88% success rate of the system developed using an ANN with the multi-layer perceptron (MLP) architecture, in performing the difficult automated preliminary detection of the tumours, even in the robust clinical test images with other biliary diseases present.
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