Deep ensemble models with multiscale lung-focused patches for pneumonia classification on chest X-ray
In person: 23 February 2022 • 5:30 PM - 7:00 PM PST
Recently, deep learning-based pneumonia classification has shown excellent performance on chest X-ray images, but when analyzing classification results through visualization, it has limitations in classifying by observing the outside of the lungs. In this study, we propose a deep ensemble model with multi-scale lung-focused patches for the classification of pneumonia. The proposed method consists of three steps: contrast enhancement, multi-scale lung-focused patches generation, and deep ensemble model with Convolutional Block Attention Module. The model trained on the large and middle-sized patches improved classification performance with an accuracy of 92% and Grad-CAM visualization showed the model focused on the lung region properly.
Seoul Women's Univ. (Korea, Republic of)
Yoon Jo Kim received the B.S. from the Digital Media, Seoul Women’s University in 2021, Korea.