4 citations · 14 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
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…
Automated Detection of COVID-19 from CT Scans Using Convolutional Neural Networks
Rohit Lokwani, Ashrika Gaikwad, Viraj Kulkarni +2
COVID-19 is an infectious disease that causes respiratory problems similar to those caused by SARS-CoV (2003). Currently, swab samples are being used for its diagnosis. The most co…
Automatic Grading of Knee Osteoarthritis on the Kellgren-Lawrence Scale from Radiographs Using Convolutional Neural Networks
Sudeep Kondal, Viraj Kulkarni, Ashrika Gaikwad +2
The severity of knee osteoarthritis is graded using the 5-point Kellgren-Lawrence (KL) scale where healthy knees are assigned grade 0, and the subsequent grades 1-4 represent incre…