3 papers
eess.IV2021
Chest X-Ray Bone Suppression for Improving Classification of Tuberculosis-Consistent Findings
Sivaramakrishnan Rajaraman, Ghada Zamzmi, Les Folio +2
Chest X-rays are the most commonly performed diagnostic examination to detect cardiopulmonary abnormalities. However, the presence of bony structures such as ribs and clavicles can…
cs.CV2021
Improved Semantic Segmentation of Tuberculosis-consistent findings in Chest X-rays Using Augmented Training of Modality-specific U-Net Models with Weak Localizations
Sivaramakrishnan Rajaraman, Les Folio, Jane Dimperio +2
Deep learning (DL) has drawn tremendous attention in object localization and recognition for both natural and medical images. U-Net segmentation models have demonstrated superior p…
eess.IV2020
Iteratively Pruned Deep Learning Ensembles for COVID-19 Detection in Chest X-rays
Sivaramakrishnan Rajaraman, Jen Siegelman, Philip O. Alderson +3
We demonstrate use of iteratively pruned deep learning model ensembles for detecting pulmonary manifestation of COVID-19 with chest X-rays. This disease is caused by the novel Seve…