Search Results for author: Iulian Emil Tampu

Found 2 papers, 1 papers with code

Inflation of test accuracy due to data leakage in deep learning-based classification of OCT images

1 code implementation21 Feb 2022 Iulian Emil Tampu, Anders Eklund, Neda Haj-Hosseini

In this study, the effect of improper dataset splitting on model evaluation is demonstrated for two classification tasks using two OCT open-access datasets extensively used in the literature, Kermany's ophthalmology dataset and AIIMS breast tissue dataset.


Does anatomical contextual information improve 3D U-Net based brain tumor segmentation?

no code implementations26 Oct 2020 Iulian Emil Tampu, Neda Haj-Hosseini, Anders Eklund

The BraTS2020 dataset was used to train and test two standard 3D U-Net models that, in addition to the conventional MR image modalities, used the anatomical contextual information as extra channels in the form of binary masks (CIM) or probability maps (CIP).

Anatomy Brain Tumor Segmentation +2

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