4 citations · 14 across the 9 of their papers we have counts for
6 papers · 1 filter
Levels of Autonomous Radiology
Suraj Ghuwalewala, Viraj Kulkarni, Richa Pant +1
Radiology, being one of the younger disciplines of medicine with a history of just over a century, has witnessed tremendous technological advancements and has revolutionized the wa…
Vulnerability Due to Training Order in Split Learning
Harshit Madaan, Manish Gawali, Viraj Kulkarni +1
Split learning (SL) is a privacy-preserving distributed deep learning method used to train a collaborative model without the need for sharing of patient's raw data between clients.…
Reducing Labelled Data Requirement for Pneumonia Segmentation using Image Augmentations
Jitesh Seth, Rohit Lokwani, Viraj Kulkarni +2
Deep learning semantic segmentation algorithms can localise abnormalities or opacities from chest radiographs. However, the task of collecting and annotating training data is expen…
Key Technology Considerations in Developing and Deploying Machine Learning Models in Clinical Radiology Practice
Viraj Kulkarni, Manish Gawali, Amit Kharat
The use of machine learning to develop intelligent software tools for interpretation of radiology images has gained widespread attention in recent years. The development, deploymen…
Comparative Evaluation of 3D and 2D Deep Learning Techniques for Semantic Segmentation in CT Scans
Abhishek Shivdeo, Rohit Lokwani, Viraj Kulkarni +2
Image segmentation plays a pivotal role in several medical-imaging applications by assisting the segmentation of the regions of interest. Deep learning-based approaches have been w…
Deep Learning Models for Calculation of Cardiothoracic Ratio from Chest Radiographs for Assisted Diagnosis of Cardiomegaly
Tanveer Gupte, Mrunmai Niljikar, Manish Gawali +3
We propose an automated method based on deep learning to compute the cardiothoracic ratio and detect the presence of cardiomegaly from chest radiographs. We develop two separate mo…