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Comparison between Different Approaches for the Creation of the Training Set: How Clustering and Dimensionality Impact the Performance of a Deep Learning Model., , , , , и . BIBE, стр. 393-396. IEEE, (2023)Comparison of different classifiers to recognize active bone marrow from CT images., , , , , , , , и . MeMeA, стр. 1-5. IEEE, (2020)Impact of network parameters on a U-Net based system for rectal cancer segmentation on MR images., , , , , и . MeMeA, стр. 1-6. IEEE, (2022)A Deep Learning model to segment liver metastases on CT images acquired at different time-points during chemotherapy., , , , , , и . MeMeA, стр. 1-6. IEEE, (2022)Deep learning model for automatic prostate segmentation on bicentric T2w images with and without endorectal coil., , , , , , , , , и . EMBC, стр. 3370-3373. IEEE, (2021)A fully automatic deep learning algorithm to segment rectal Cancer on MR images: a multi-center study., , , , , , , , , и 1 other автор(ы). EMBC, стр. 5066-5069. IEEE, (2022)A Convolutional Neural Network based system for Colorectal cancer segmentation on MRI images., , , , , , , , и . EMBC, стр. 1675-1678. IEEE, (2020)Deep learning to segment liver metastases on CT images: impact on a radiomics method to predict response to chemotherapy., , , , , , , , и . MeMeA, стр. 1-5. IEEE, (2020)Comparison of radiomics approaches to predict resistance to 1st line chemotherapy in liver metastatic colorectal cancer., , , , , , , , , и 2 other автор(ы). EMBC, стр. 3305-3308. IEEE, (2021)An innovative radiomics approach to predict response to chemotherapy of liver metastases based on CT images., , , , , , , и . EMBC, стр. 1339-1342. IEEE, (2020)