27 citations · 90 across the 11 of their papers we have counts for
4 papers · 1 filter
Automatic Labels are as Effective as Manual Labels in Biomedical Images Classification with Deep Learning
Niccolò Marini, Stefano Marchesin, Lluis Borras Ferris +12
The increasing availability of biomedical data is helping to design more robust deep learning (DL) algorithms to analyze biomedical samples. Currently, one of the main limitations…
Improving Quality Control of Whole Slide Images by Explicit Artifact Augmentation
Artur Jurgas, Marek Wodzinski, Marina D'Amato +3
The problem of artifacts in whole slide image acquisition, prevalent in both clinical workflows and research-oriented settings, necessitates human intervention and re-scanning. Ove…
RegWSI: Whole Slide Image Registration using Combined Deep Feature- and Intensity-Based Methods: Winner of the ACROBAT 2023 Challenge
Marek Wodzinski, Niccolò Marini, Manfredo Atzori +1
The automatic registration of differently stained whole slide images (WSIs) is crucial for improving diagnosis and prognosis by fusing complementary information emerging from diffe…
DeeperHistReg: Robust Whole Slide Images Registration Framework
Marek Wodzinski, Niccolò Marini, Manfredo Atzori +1
DeeperHistReg is a software framework dedicated to registering whole slide images (WSIs) acquired using multiple stains. It allows one to perform the preprocessing, initial alignme…