1 citations · 1 across the 6 of their papers we have counts for
6 papers
Random Direct Preference Optimization for Radiography Report Generation
Valentin Samokhin, Boris Shirokikh, Mikhail Goncharov +5
Radiography Report Generation (RRG) has gained significant attention in medical image analysis as a promising tool for alleviating the growing workload of radiologists. However, de…
Medical Semantic Segmentation with Diffusion Pretrain
David Li, Anvar Kurmukov, Mikhail Goncharov +2
Recent advances in deep learning have shown that learning robust feature representations is critical for the success of many computer vision tasks, including medical image segmenta…
Anatomical Positional Embeddings
Mikhail Goncharov, Valentin Samokhin, Eugenia Soboleva +5
We propose a self-supervised model producing 3D anatomical positional embeddings (APE) of individual medical image voxels. APE encodes voxels' anatomical closeness, i.e., voxels of…
vox2vec: A Framework for Self-supervised Contrastive Learning of Voxel-level Representations in Medical Images
Mikhail Goncharov, Vera Soboleva, Anvar Kurmukov +2
This paper introduces vox2vec - a contrastive method for self-supervised learning (SSL) of voxel-level representations. vox2vec representations are modeled by a Feature Pyramid Net…
CT-based COVID-19 Triage: Deep Multitask Learning Improves Joint Identification and Severity Quantification
Mikhail Goncharov, Maxim Pisov, Alexey Shevtsov +8
The current COVID-19 pandemic overloads healthcare systems, including radiology departments. Though several deep learning approaches were developed to assist in CT analysis, nobody…
Incorporating Task-Specific Structural Knowledge into CNNs for Brain Midline Shift Detection
Maxim Pisov, Mikhail Goncharov, Nadezhda Kurochkina +9
Midline shift (MLS) is a well-established factor used for outcome prediction in traumatic brain injury, stroke and brain tumors. The importance of automatic estimation of MLS was r…