A Comprehensive Survey of Pneumonia Diagnosis: Image Processing and Deep Learning Advancements

Pneumonia is a major global health concern, and early, accurate diagnosis is crucial for effective treatment and better patient outcomes. Recent advances in medical imaging and deep learning have transformed pneumonia diagnosis. This comprehensive survey explores the latest methods and innovations in pneumonia diagnosis, with a focus on image processing and deep learning. It provides background information on pneumonia, its challenges, and the role of medical imaging in improving diagnosis. The survey covers different imaging modalities, such as chest X-rays and CT scans, and discusses image pre-processing techniques, including lung segmentation. It also delves into deep learning models like Convolutional Neural Networks (CNNs) and their application in medical image analysis. The survey categorizes and analyzes research works on various topics related to pneumonia diagnosis, highlighting trends, commonalities, and gaps in existing research. This study offers a comprehensive overview of advancements in pneumonia diagnosis through image processing and deep learning, serving as a valuable resource for researchers, clinicians, and healthcare professionals interested in this field’s current status and future directions.