论文标题
使用小波变换和转移学习的胸部疾病分类
Classification of Chest Diseases using Wavelet Transforms and Transfer Learning
论文作者
论文摘要
胸部X射线扫描是放射科医生最常使用的方式，可以在其初始阶段诊断许多胸部相关疾病。拟议的系统有助于放射科医生对扫描中发现的疾病的决定更有效。我们的系统结合了图像处理的技术，以增强特征和深度学习，以进行疾病之间的分类。我们已经使用了ChestX-Ray14数据库，以训练我们在其中发现的14种不同标记疾病的深度学习模型。拟议的研究表明，通过使用小波变换作为预处理技术，结果显着改善。
Chest X-ray scan is a most often used modality by radiologists to diagnose many chest related diseases in their initial stages. The proposed system aids the radiologists in making decision about the diseases found in the scans more efficiently. Our system combines the techniques of image processing for feature enhancement and deep learning for classification among diseases. We have used the ChestX-ray14 database in order to train our deep learning model on the 14 different labeled diseases found in it. The proposed research shows the significant improvement in the results by using wavelet transforms as pre-processing technique.
