Classification of Chest Diseases using Wavelet Transforms and Transfer Learning
- Resource Type
- Working Paper
- Authors
- Rasheed, Ahmed; Younis, Muhammad Shahzad; Bilal, Muhammad; Rasheed, Maha
- Source
- Subject
- Electrical Engineering and Systems Science - Image and Video Processing
Computer Science - Computer Vision and Pattern Recognition
Computer Science - Machine Learning
- Language
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.
Comment: 8 pages, 4 figures, Presented in International Conference On Medical Imaging And Computer-Aided Diagnosis (MICAD 2020), proceeding will be published with Springer in their "Lecture Notes in Electrical Engineering (LNEE)" (ISSN: 1876-1100)