Trefwoorden:
Alle publicaties voor Niccolò Marini
2025
| , , , , , , , , , en , Automatic labels are as effective as manual labels in digital pathology images classification with deep learning (2025), in: Journal of Pathology Informatics(100462) |
2024
| , , , , , , , en , A full pipeline to analyze lung histopathology images, in: Digital and Computational Pathology, SPIE Medical Imaging, 2024 |
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| , , , , en , A multi-scale CNN for transfer learning in sEMG-based hand gesture recognition for prosthetic devices (2024), in: Sensors, 24:22(7147) |
| , , , , , en , A systematic comparison of deep learning methods for Gleason grading and scoring (2024), in: Medical Image Analysis |
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| , , , , , , , , , , en , Automated classification of celiac disease in histopathological images: a multi-scale approach, in: Computer-Aided Diagnosis, SPIE Medical Imaging, 2024 |
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| , , , , , , , , , , , en , Multimodal Representations of Biomedical Knowledge from Limited Training Whole Slide Images and Reports using Deep Learning (2024), in: Medical Image Analysis |
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| , , en , RegWSI: Whole slide image registration using combined deep feature- and intensity-based methods: Winner of the ACROBAT 2023 challenge (2024), in: Computer Methods and Programs in Biomedicine |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , en , The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue (2024), in: Medical Image Analysis |
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2023
| , , , , , , , , , en , Data-driven color augmentation for H\&E stained images in computational pathology (2023), in: Journal of Pathology Informatics(100183) |
| , , , , en , Explanation Generation via Decompositional Rules Extraction for Head and Neck Cancer Classification, in: Explainable and Transparent AI and Multi-Agent Systems, 2023 |
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| , , , , , , , , , , , en , Modelling digital health data: The ExaMode ontology for computational pathology (2023), in: PMC |
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| , , , , , , , , en , On-cloud decision-support system for non-small cell lung cancer histology characterization from thorax computed tomography scans, Computerized Medical Imaging and Graphics (2023), in: Comput Med Imaging Graph . |
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2022
| , , , , , , en , A DEXiRE for Extracting Propositional Rules from Neural Networks via Binarization (2022), in: MDPI Electronics, 11:24 |
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| , , en , A multi-task Multiple Instance Learning algorithm to analyze large whole slide images from the BRIGHT challenge 2022, in: ISBI Challenges 2022, Bangalore India, 2022 |
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| , , , , en , Attention-based Interpretable Regression of Gene Expression in Histology, in: Proceedings of the The Workshop on Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC) at MICCAI 2022, 2022 |
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| , , , , , , , , , , , , en , Empowering Digital Pathology Applications through Explainable Knowledge Extraction Tools (2022), in: Journal of Digital Pathology |
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| , , , , , , en , stainlib: a python library for augmentation and normalization of histopathology H&E images (2022), in: bioArXiv |
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| , , , , , , , , , , , , , , , , , , en , Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations (2022), in: Nature Partner Journal on Digital Medicine |
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| , , , en , Unsupervised Deep Network for Large Deformations followed by Instance Optimization and Objective Function Weighting by Inverse Consistency: Contribution to the BraTS-Reg Challenge, in: MICCAI BrainLes workshop, 2022 |
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2021
| , , en , Combining weak and strong supervised learning improves strong supervision in Gleason pattern classification (2021), in: BMC Medical Imaging |
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| , , , en , H&E-adversarial network: a convolutional neural network to learn stain-invariant features through Hematoxylin & Eosin regression, in: ICCV 2021 workshop on Computational Challenges in Digital Pathology, 2021 |
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| , , , , , , , en , Multi-Scale Multiple Instance Learning for the Classification of Digital Pathology Images with Global Annotations, in: COMPAY workshop at MICCAI, 2021 |
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| , , , , , , en , Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images (2021), in: Frontiers in Computer Science |
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| , , en , Semi-supervised learning with a teacher-student paradigm for histopathology classification: a resource to face data heterogeneity and lack of local annotations, in: Workshop Artificial Intelligence for Digital Pathology, ICPR, Milano, Italy, 2021 |
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| , , en , Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: an experiment on histopathology image classification (2021), in: Medical Image Analysis |
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2020
| , , en , Semi-Weakly Supervised Learning for Prostate Cancer Image Classification with Teacher-Student Deep Convolutional Networks, in: MICCAI workshop Labels, Lima, Peru, 2020 |
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