309 citations · 311 across the 10 of their papers we have counts for
7 papers · 1 filter
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…
Anatomy of Domain Shift Impact on U-Net Layers in MRI Segmentation
Ivan Zakazov, Boris Shirokikh, Alexey Chernyavskiy +1
Domain Adaptation (DA) methods are widely used in medical image segmentation tasks to tackle the problem of differently distributed train (source) and test (target) data. We consid…
Multi-domain CT Metal Artifacts Reduction Using Partial Convolution Based Inpainting
Artem Pimkin, Alexander Samoylenko, Natalia Antipina +4
Recent CT Metal Artifacts Reduction (MAR) methods are often based on image-to-image convolutional neural networks for adjustment of corrupted sinograms or images themselves. In thi…
Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge
Hugo J. Kuijf, J. Matthijs Biesbroek, Jeroen de Bresser +41
Quantification of cerebral white matter hyperintensities (WMH) of presumed vascular origin is of key importance in many neurological research studies. Currently, measurements are o…
Brain Tumor Image Retrieval via Multitask Learning
Maxim Pisov, Gleb Makarchuk, Valery Kostjuchenko +3
Classification-based image retrieval systems are built by training convolutional neural networks (CNNs) on a relevant classification problem and using the distance in the resulting…
Tumor Delineation For Brain Radiosurgery by a ConvNet and Non-Uniform Patch Generation
Egor Krivov, Valery Kostjuchenko, Alexandra Dalechina +5
Deep learning methods are actively used for brain lesion segmentation. One of the most popular models is DeepMedic, which was developed for segmentation of relatively large lesions…