Research Publications – Page 8

Evaluating patients with pulmonary thromboembolism: a retrospective study on the utilization of serum D-dimer assay and CT angiography

Abstract Background and objective: Serum D-dimer assay is an inexpensive laboratory test with a high negative predictive value, obviating the need for computed tomographic pulmonary angiography (CTPA) in patients with low clinical probability of thromboembolic disease. It has been recommended that CTPA may be performed only in patients with positive D-dimer assays and clinical suspicion of PTE (pulmonary […]

Evaluating patients with pulmonary thromboembolism: a retrospective study on the utilization of serum D-dimer assay and CT angiography Read More »

Validation of expert system enhanced deep learning algorithm for automated screening for COVID-Pneumonia on chest X-rays

Abstract The coronavirus disease of 2019 (COVID-19) pandemic exposed a limitation of artificial intelligence (AI) based medical image interpretation systems. Early in the pandemic, when need was greatest, the absence of sufficient training data prevented effective deep learning (DL) solutions. Even now, there is a need for Chest-X-ray (CxR) screening tools in low and middle

Validation of expert system enhanced deep learning algorithm for automated screening for COVID-Pneumonia on chest X-rays Read More »

Interobserver Variation in Response Evaluation Criteria in Solid Tumors

Abstract Purpose: Response Evaluation Criteria in Solid Tumors (RECIST 1.1) is the gold standard for imaging response evaluation in cancer trials. We sought to evaluate consistency of applying RECIST 1.1 between 2 conventionally trained radiologists, designated as A and B; identify reasons for variation; and reconcile these differences for future studies. Methods: The study was approved as

Interobserver Variation in Response Evaluation Criteria in Solid Tumors Read More »

Pneumothorax Detection and Classification on Chest Radiographs using Artificial Intelligence

Abstract In recent years, Computer Aided Diagnosis (CAD) systems have been designed for the detection of lung space anomalies.Pneumothorax is an abnormal collection of air in the pleural space between the lung and the chest wall that can result inpartial or complete lung collapse [1]. This is a medical emergency in which quick detection and

Pneumothorax Detection and Classification on Chest Radiographs using Artificial Intelligence Read More »

Pneumonia Detection and Classification on Chest Radiographs using Deep Learning

Abstract Computer Aided Diagnosis (CAD) is progressively becoming a reliable tool in enhancing the productivity and accuracy of a radiologist in detecting abnormalities on chest radiographs. Detection of airspace disease such as pneumonia can be facilitated with the help of image processing and deep learning algorithms. In this study, we aim to develop and evaluate

Pneumonia Detection and Classification on Chest Radiographs using Deep Learning Read More »