Pneumonia Detection and Severity Classification in Chest X-Rays through Region Based Isolation and Optimized CNN Architectures
Year: 2025
Type: article
Abstract: - Globally, pneumonia is still a major health concern, particularly in areas with poor diagnostic facilities. This paper compares two CNN architectures, ConvXNet and a CustomCNN, for deep learning-based pneumonia identification using chest X-ray pictures. Preprocessing methods were used, including data augmentation, contrast enhancement, normalization, and grayscale conversion. A segmentation framework based on U-Net and ResNet32 was also implemented in order to separate lung regions and extract information unique to each region.
Authors: Kandyala Yaswanth Sai, Chinta Swathi, Chakali Yeswanth Kumar, Veliginti Vedavyas
Language: English
Topic: COVID-19 diagnosis using AI
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4411501313