no code implementations • 1 Oct 2021 • Sumeet Menon, Jayalakshmi Mangalagiri, Josh Galita, Michael Morris, Babak Saboury, Yaacov Yesha, Yelena Yesha, Phuong Nguyen, Aryya Gangopadhyay, David Chapman
CCS-GAN achieves high accuracy with few positive images and thereby greatly reduces the barrier of acquiring large training volumes in order to train a diagnostic classifier for COVID-19.
no code implementations • 2 Apr 2021 • Jayalakshmi Mangalagiri, David Chapman, Aryya Gangopadhyay, Yaacov Yesha, Joshua Galita, Sumeet Menon, Yelena Yesha, Babak Saboury, Michael Morris, Phuong Nguyen
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 approximations and with the potential to generate full synthetic 3D scan volumes.
no code implementations • 19 Oct 2020 • Kushal Mehta, Arshita Jain, Jayalakshmi Mangalagiri, Sumeet Menon, Phuong Nguyen, David R. Chapman
Our algorithm employs a 3D Convolutional Neural Network (CNN) as well as a Random Forest in order to combine CT imagery with biomarker annotation and volumetric radiomic features.
no code implementations • 26 Sep 2020 • Sumeet Menon, Joshua Galita, David Chapman, Aryya Gangopadhyay, Jayalakshmi Mangalagiri, Phuong Nguyen, Yaacov Yesha, Yelena Yesha, Babak Saboury, Michael Morris
We present a novel Mean Teacher + Transfer GAN (MTT-GAN) that generates COVID19 chest X-ray images of high quality.