Background: Chest X-Ray (CXR) is routinely used as the primary diagnostic technique in chest trauma but some possibly life-threatening injuries are repeatedly missed on CXR. Non contrast computed tomography (NCCT) scan a superior device blunt chest. Aim: To compare efficacy of x-ray versus NCCT diagnosis Methodology: The present cross sectional study was performed admitted patients causality Su...

Background: Radiologists used chest radiographs to detect coronavirus disease 2019 (COVID-19) in patients and determine the severity levels. The COVID-19 cases were grouped into five classes, each receiving different treatments. An intelligent system is needed advance detection identify vector features of X-ray images with a quality that too poor be read by radiologists. Deep learning an can th...

Recent advances in deep learning have led to a promising performance many medical image analysis tasks. As the most commonly performed radiological exam, chest radiographs are particularly important modality for which variety of applications been researched. The release multiple, large, publicly available X-ray datasets recent years has encouraged research interest and boosted number publicatio...

This work presents an application of different deep learning related paradigms to the diagnosis multiple chest pathologies. Within article, a well-known Convolutional Neural Network (DenseNet) is used and fine-tuned for X-Ray medical tasks. Different image augmentation methods are applied over training images improve performance resulting model as well incorporation explainability layer highlig...