Negar Abbasi

Research project: Enhancing Pulmonary Disease Diagnosis with Deep Learning: A Path to Precision Medicine

Abstract

Deep learning techniques are revolutionizing the field of medical imaging, especially in enhancing the diagnosis of pulmonary diseases such as tuberculosis. These methods facilitate timely and accurate disease detection, crucial for effective treatment. Despite their success, challenges persist, particularly in handling complex chest X-ray (CXR) images where infections complicate image analysis. Current deep learning models struggle with capturing both local and global feature relationships and are often hindered by poor data quality, leading to lower accuracy in disease classification. This PhD project aims to tackle these issues by developing robust deep learning approaches that improve pulmonary disease classification and contribute to the broader implementation of deep learning models in the field.