9 citations · 9 across the 4 of their papers we have counts for
5 papers
CCS-GAN: COVID-19 CT-scan classification with very few positive training images
Sumeet Menon, Jayalakshmi Mangalagiri, Josh Galita +7
We present a novel algorithm that is able to classify COVID-19 pneumonia from CT Scan slices using a very small sample of training images exhibiting COVID-19 pneumonia in tandem wi…
Toward Generating Synthetic CT Volumes using a 3D-Conditional Generative Adversarial Network
Jayalakshmi Mangalagiri, David Chapman, Aryya Gangopadhyay +7
We present a novel conditional Generative Adversarial Network (cGAN) architecture that is capable of generating 3D Computed Tomography scans in voxels from noisy and/or pixelated a…
Lung Nodule Classification Using Biomarkers, Volumetric Radiomics and 3D CNNs
Kushal Mehta, Arshita Jain, Jayalakshmi Mangalagiri +3
We present a hybrid algorithm to estimate lung nodule malignancy that combines imaging biomarkers from Radiologist's annotation with image classification of CT scans. Our algorithm…
Deep Expectation-Maximization for Semi-Supervised Lung Cancer Screening
Sumeet Menon, David Chapman, Phuong Nguyen +3
We present a semi-supervised algorithm for lung cancer screening in which a 3D Convolutional Neural Network (CNN) is trained using the Expectation-Maximization (EM) meta-algorithm.…
Generating Realistic COVID19 X-rays with a Mean Teacher + Transfer Learning GAN
Sumeet Menon, Joshua Galita, David Chapman +7
COVID-19 is a novel infectious disease responsible for over 800K deaths worldwide as of August 2020. The need for rapid testing is a high priority and alternative testing strategie…