7 citations · 9 across the 7 of their papers we have counts for
4 papers · 1 filter
Negligible effect of brain MRI data preprocessing for tumor segmentation
Ekaterina Kondrateva, Polina Druzhinina, Alexandra Dalechina +5
Magnetic resonance imaging (MRI) data is heterogeneous due to differences in device manufacturers, scanning protocols, and inter-subject variability. A conventional way to mitigate…
Systematic Clinical Evaluation of A Deep Learning Method for Medical Image Segmentation: Radiosurgery Application
Boris Shirokikh, Alexandra Dalechina, Alexey Shevtsov +6
We systematically evaluate a Deep Learning (DL) method in a 3D medical image segmentation task. Our segmentation method is integrated into the radiosurgery treatment process and di…
Universal Loss Reweighting to Balance Lesion Size Inequality in 3D Medical Image Segmentation
Boris Shirokikh, Alexey Shevtsov, Anvar Kurmukov +5
Target imbalance affects the performance of recent deep learning methods in many medical image segmentation tasks. It is a twofold problem: class imbalance - positive class (lesion…
Deep Learning for Brain Tumor Segmentation in Radiosurgery: Prospective Clinical Evaluation
Boris Shirokikh, Alexandra Dalechina, Alexey Shevtsov +7
Stereotactic radiosurgery is a minimally-invasive treatment option for a large number of patients with intracranial tumors. As part of the therapy treatment, accurate delineation o…