8 citations · 14 across the 3 of their papers we have counts for
3 papers
eess.IV2021
End-to-end lung nodule detection framework with model-based feature projection block
Ivan Drokin, Elena Ericheva
This paper proposes novel end-to-end framework for detecting suspicious pulmonary nodules in chest CT scans. The method core idea is a new nodule segmentation architecture with a m…
eess.IV2020★ 6 cited
Deep Learning on Point Clouds for False Positive Reduction at Nodule Detection in Chest CT Scans
Ivan Drokin, Elena Ericheva
This paper focuses on a novel approach for false-positive reduction (FPR) of nodule candidates in Computer-aided detection (CADe) systems following the suspicious lesions detection…
eess.IV2019★ 8 cited
GANs 'N Lungs: improving pneumonia prediction
Tatiana Malygina, Elena Ericheva, Ivan Drokin
We propose a novel method to improve deep learning model performance on highly-imbalanced tasks. The proposed method is based on CycleGAN to achieve balanced dataset. We show that…