4 papers
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…
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…