21 citations · 22 across the 4 of their papers we have counts for
4 papers
Uncovering the effects of model initialization on deep model generalization: A study with adult and pediatric Chest X-ray images
Sivaramakrishnan Rajaraman, Ghada Zamzmi, Feng Yang +3
Model initialization techniques are vital for improving the performance and reliability of deep learning models in medical computer vision applications. While much literature exist…
Semantically Redundant Training Data Removal and Deep Model Classification Performance: A Study with Chest X-rays
Sivaramakrishnan Rajaraman, Ghada Zamzmi, Feng Yang +3
Deep learning (DL) has demonstrated its innate capacity to independently learn hierarchical features from complex and multi-dimensional data. A common understanding is that its per…
Does image resolution impact chest X-ray based fine-grained Tuberculosis-consistent lesion segmentation?
Sivaramakrishnan Rajaraman, Feng Yang, Ghada Zamzmi +2
Deep learning (DL) models are state-of-the-art in segmenting anatomical and disease regions of interest (ROIs) in medical images. Particularly, a large number of DL-based technique…
A bone suppression model ensemble to improve COVID-19 detection in chest X-rays
Sivaramakrishnan Rajaraman, Gregg Cohen, Lillian Spear +2
Chest X-ray (CXR) is a widely performed radiology examination that helps to detect abnormalities in the tissues and organs in the thoracic cavity. Detecting pulmonary abnormalities…