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eess.IV2025
Integrating Radiomics with Deep Learning Enhances Multiple Sclerosis Lesion Delineation
Nadezhda Alsahanova, Pavel Bartenev, Maksim Sharaev +3
Background: Accurate lesion segmentation is critical for multiple sclerosis (MS) diagnosis, yet current deep learning approaches face robustness challenges. Aim: This study improve…
eess.IV2019
Weakly Supervised Fine Tuning Approach for Brain Tumor Segmentation Problem
Sergey Pavlov, Alexey Artemov, Maksim Sharaev +2
Segmentation of tumors in brain MRI images is a challenging task, where most recent methods demand large volumes of data with pixel-level annotations, which are generally costly to…
eess.IV2019
3D Deformable Convolutions for MRI classification
Marina Pominova, Ekaterina Kondrateva, Maksim Sharaev +3
Deep learning convolutional neural networks have proved to be a powerful tool for MRI analysis. In current work, we explore the potential of the deformable convolutional deep neura…