Niccolò Marini

Orcid: 0000-0002-5273-5741

According to our database1, Niccolò Marini authored at least 14 papers between 2020 and 2023.

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Bibliography

2023
On-cloud decision-support system for non-small cell lung cancer histology characterization from thorax computed tomography scans.
Comput. Medical Imaging Graph., December, 2023

Deep learning methods to reduce the need for annotations for the extraction of knowledge from multimodal heterogeneous medical data.
PhD thesis, 2023

The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue.
CoRR, 2023

Explanation Generation via Decompositional Rules Extraction for Head and Neck Cancer Classification.
Proceedings of the Explainable and Transparent AI and Multi-Agent Systems, 2023

2022
Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations.
npj Digit. Medicine, 2022

Attention-Based Interpretable Regression of Gene Expression in Histology.
Proceedings of the Interpretability of Machine Intelligence in Medical Image Computing, 2022

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.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2022

2021
Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification.
Medical Image Anal., 2021

Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images.
Frontiers Comput. Sci., 2021

Combining weakly and strongly supervised learning improves strong supervision in Gleason pattern classification.
BMC Medical Imaging, 2021

H&E-adversarial network: a convolutional neural network to learn stain-invariant features through Hematoxylin & Eosin regression.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Multi-Scale Task Multiple Instance Learning for the Classification of Digital Pathology Images with Global Annotations.
Proceedings of the MICCAI Workshop on Computational Pathology, 2021

2020
Semi-weakly Supervised Learning for Prostate Cancer Image Classification with Teacher-Student Deep Convolutional Networks.
Proceedings of the Interpretable and Annotation-Efficient Learning for Medical Image Computing, 2020

Semi-supervised Learning with a Teacher-Student Paradigm for Histopathology Classification: A Resource to Face Data Heterogeneity and Lack of Local Annotations.
Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020


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