Ivan Ezhov
Technical University of Munich(DE)
Publications by Year
Research Areas
Radiomics and Machine Learning in Medical Imaging, Brain Tumor Detection and Classification, Glioma Diagnosis and Treatment, Advanced Neural Network Applications, Medical Image Segmentation Techniques
Most-Cited Works
- → The Liver Tumor Segmentation Benchmark (LiTS)(2022)1,081 cited
- → VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images(2021)333 cited
- → Federated learning enables big data for rare cancer boundary detection(2022)313 cited
- → ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset(2022)155 cited
- → An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset(2021)115 cited
- → BraTS Toolkit: Translating BraTS Brain Tumor Segmentation Algorithms Into Clinical and Scientific Practice(2020)108 cited
- → Markov Processes with Homogeneous Second Component. I