4 citations · 5 across the 3 of their papers we have counts for
3 papers
Pediatric brain tumor classification using digital histopathology and deep learning: evaluation of SOTA methods on a multi-center Swedish cohort
Iulian Emil Tampu, Per Nyman, Christoforos Spyretos +7
Brain tumors are the most common solid tumors in children and young adults, but the scarcity of large histopathology datasets has limited the application of computational pathology…
Inflation of test accuracy due to data leakage in deep learning-based classification of OCT images
Iulian Emil Tampu, Anders Eklund, Neda Haj-Hosseini
In the application of deep learning on optical coherence tomography (OCT) data, it is common to train classification networks using 2D images originating from volumetric data. Give…
Does anatomical contextual information improve 3D U-Net based brain tumor segmentation?
Iulian Emil Tampu, Neda Haj-Hosseini, Anders Eklund
Effective, robust, and automatic tools for brain tumor segmentation are needed for the extraction of information useful in treatment planning from magnetic resonance (MR) images. C…