USAGE OF ARTIFICIAL NEURAL NETWORKS IN THE DIAGNOSIS OF KNEE JOINT DISORDERS

Konrad Witkowski, Mikołaj Wieczorek
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Abstract

Following article address the issue of automatic knee disorder diagnose with usage of neural networks. We proposed several hybrid neural net architectures which aim to successfully classify abnormality using MRI (magnetic resonance imaging) images acquired from publicly available dataset. To construct such combinations of models we used pretrained Alexnet, Resnet18 and Resnet34 downloaded from Torchvision. Experiments showed that for certain abnormalities our models can achieve up to 90% accuracy.
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人工神经网络在膝关节疾病诊断中的应用
以下文章探讨了利用神经网络自动诊断膝关节疾病的问题。我们提出了几种混合神经网络架构,旨在利用从公开数据集获取的 MRI(磁共振成像)图像成功地对异常情况进行分类。为了构建这样的模型组合,我们使用了从 Torchvision 下载的预训练 Alexnet、Resnet18 和 Resnet34。实验表明,对于某些异常情况,我们的模型可以达到 90% 的准确率。
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