27 citations · 79 across the 10 of their papers we have counts for
10 papers
FRED: The Florence RGB-Event Drone Dataset
Gabriele Magrini, Niccolò Marini, Federico Becattini +4
Small, fast, and lightweight drones present significant challenges for traditional RGB cameras due to their limitations in capturing fast-moving objects, especially under challengi…
Green AI: Which Programming Language Consumes the Most?
Niccolò Marini, Leonardo Pampaloni, Filippo Di Martino +2
AI is demanding an evergrowing portion of environmental resources. Despite their potential impact on AI environmental sustainability, the role that programming languages play in AI…
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…
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…
The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue
Philippe Weitz, Masi Valkonen, Leslie Solorzano +38
The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications. Advances in computing, deep learning, and availability…
Unsupervised Method for Intra-patient Registration of Brain Magnetic Resonance Images based on Objective Function Weighting by Inverse Consistency: Contribution to the BraTS-Reg Challenge
Marek Wodzinski, Artur Jurgas, Niccolo Marini +2
Registration of brain scans with pathologies is difficult, yet important research area. The importance of this task motivated researchers to organize the BraTS-Reg challenge, joint…
Attention-based Interpretable Regression of Gene Expression in Histology
Mara Graziani, Niccolò Marini, Nicolas Deutschmann +3
Interpretability of deep learning is widely used to evaluate the reliability of medical imaging models and reduce the risks of inaccurate patient recommendations. For models exceed…
H&E-adversarial network: a convolutional neural network to learn stain-invariant features through Hematoxylin & Eosin regression
Niccoló Marini, Manfredo Atzori, Sebastian Otálora +2
Computational pathology is a domain that aims to develop algorithms to automatically analyze large digitized histopathology images, called whole slide images (WSI). WSIs are produc…
The Brain Tumor Sequence Registration (BraTS-Reg) Challenge: Establishing Correspondence Between Pre-Operative and Follow-up MRI Scans of Diffuse Glioma Patients
Bhakti Baheti, Satrajit Chakrabarty, Hamed Akbari +70
Registration of longitudinal brain MRI scans containing pathologies is challenging due to dramatic changes in tissue appearance. Although there has been progress in developing gene…