Niccolò Marini - HES SO Valais Publications

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Vorname(n):	Niccolò
Nachname(n):	Marini

Lluis Borràs Ferrís, Simon Püttmann, Niccolò Marini, Simona Vatrano, Filippo Fragetta, Alessandro Caputo, Francesco Ciompi, Manfredo Atzori und Henning Müller, A full pipeline to analyze lung histopathology images, in: Digital and Computational Pathology, SPIE Medical Imaging, 2024

[DOI]

Juan P. Dominguez-Morales, Lourdes Duran-Lopez, Niccolò Marini, Saturnino Vicente-Diaz, Alejandro Linares-Barranco, Manfredo Atzori und Henning Müller, A systematic comparison of deep learning methods for Gleason grading and scoring (2024), in: Medical Image Analysis

[DOI]

Simon Püttmann, Lluis Borràs Ferrís, Niccolò Marini, Witali Aswolinsky, Simona Vatrano, Filippo Fragetta, Iris Nagtegaal, Chella van der Post, Francesco Ciompi, Manfredo Atzori, Christoph Friedrich und Henning Müller, Automated classification of celiac disease in histopathological images: a multi-scale approach, in: Computer-Aided Diagnosis, SPIE Medical Imaging, 2024

[DOI]

Niccolò Marini, Stefano marchesin, Marek Wodzinski, Alessandro Caputo, Damian Podareanu, Bryan Cardenas Guevara, Svetla Boytcheva, Simona Vatrano, Filippo Fraggetta, Francesco Ciompi, Gianmaria Silvello, Henning Müller und Manfredo Atzori, Multimodal Representations of Biomedical Knowledge from Limited Training Whole Slide Images and Reports using Deep Learning (2024), in: Medical Image Analysis

[DOI]

Marek Wodzinski, Niccolò Marini, Manfredo Atzori und Henning Müller, 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

[DOI]

Philippe Weitz, Masi Valkonen, Leslie Solorzano, Circe Carr, Kimmo Kartasalo, Constance Boissin, Sonja Koivukoski, Aino Kuusela, Dusan Rasic, Yanbo Feng, Sandra Sinius Pouplier, Abhinav Sharma, Kajsa Ledesma Eriksson, Stephanie Robertson, Christian Marzahl, Chandler D. Gatenbee, Alexander R. A. Anderson, Marek Wodzinski, Artur Jurgas, Niccolò Marini, Manfredo Atzori, Henning Müller, Daniel Budelmann, Nick Weiss, Stefan Heldmann, Johannes Lotz, Jelmer M. Wolterink, Bruno De Santi, Abhijeet Patil, Amit Sethi, Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa, Mahtab Farrokh, Neeraj Kumar, Russell Greiner, Leena Latonen, Anne-Vibeke Laenkholm, Johan Hartman, Pekka Ruusuvuori und Mattias Rantalainen, The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue (2024), in: Medical Image Analysis

[DOI]

Niccolò Marini, Sebastian Otalora, Marek Wodzinski, Selene Tomassini, Aldo Franco Dragoni, Stéphane Marchand-Maillet, Juan Pedro Dominguez Morales, Lourdes Duran-Lopez, Simona Vatrano, Henning Müller und others, Data-driven color augmentation for H\&E stained images in computational pathology (2023), in: Journal of Pathology Informatics(100183)

Victor H. Contreras, Andrea Bagante, Niccolò Marini, Michael Schumacher, Vincent Andrearczyk und Davide Calvaresi, Explanation Generation via Decompositional Rules Extraction for Head and Neck Cancer Classification, in: Explainable and Transparent AI and Multi-Agent Systems, 2023

Laura Menotti, Gianmaria Silvello, Manfredo Atzori, Svetla Boytcheva, Francesco Ciompi, Giorgio Maria Di Nunzio, Filippo Fraggetta, Fabio Giachelle, Ornella Irrera, Stefano marchesin, Niccolò Marini, Henning Müller und Todor Primov, Modelling digital health data: The ExaMode ontology for computational pathology (2023), in: PMC

[DOI]

Selene Tomassini, Nicola Falcionelli, Bruschi Giulia, Agnese Sbrollini, Niccolò Marini, Paolo Sernani, Micaela Morettini, Henning Müller, Dragoni Franco Aldo und Laura Burattini, 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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Victor H. Contreras, Niccolò Marini, Lora Fanda, Gaetano Manzo, Yazan Mualla, Jean-Paul Calbimonte, Michael Schumacher und Davide Calvaresi, A DEXiRE for Extracting Propositional Rules from Neural Networks via Binarization (2022), in: MDPI Electronics, 11:24

[DOI]
[URL]

Niccolò Marini, Marek Wodzinski, Manfredo Atzori und Henning Müller, 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

Mara Graziani, Niccolò Marini, Nicolas Deutschmann, Nikita Janakarajan, Henning Müller und Maria Rodriguez Martinez, 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

Stefano marchesin, Fabio Giachelle, Niccolò Marini, Manfredo Atzori, Svetla Boytcheva, Genziana Buttafuoco, Francesco Ciompi, Giorgio Maria Di Nunzio, Filippo Fraggetta, Ornella Irrera, Henning Müller, Todor Primov, Simona Valtrano und Gianmaria Silvello, Empowering Digital Pathology Applications through Explainable Knowledge Extraction Tools (2022), in: Journal of Digital Pathology

Sebastian Otalora, Niccolò Marini, Damian Podareanu, Ruben Hekster, David Tellez, Jeroen van der Laak, Henning Müller und Manfredo Atzori, stainlib: a python library for augmentation and normalization of histopathology H&E images (2022), in: bioArXiv

Niccolò Marini, Stefano marchesin, Sebastian Otalora, Marek Wodzinski, Alessandro Caputo, mert van Rijthoven, Witali Aswolinskiy, John Melle Bokhorst, Damian Podareanu, Edyta Petters, Svetla Boytcheva, Genziana Buttafuoco, Simona Valtrano, Filippo Fraggetta, Uulke A. van der Heide, Maristella Agosti, Francesco Ciompi, Gianmaria Silvello, Henning Müller und Manfredo Atzori, Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations (2022), in: Nature Partner Journal on Digital Medicine

Marek Wodzinski, Artur Jurgas, Niccolò Marini, Manfredo Atzori und Henning Müller, 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

Sebastian Otalora, Niccolò Marini, Henning Müller und Manfredo Atzori, Combining weak and strong supervised learning improves strong supervision in Gleason pattern classification (2021), in: BMC Medical Imaging

Niccolò Marini, Manfredo Atzori, Sebastian Otalora, Stéphane Marchand-Maillet und Henning Müller, 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

Niccolò Marini, Sebastian Otalora, Francesco Ciompi, Gianmaria Silvello, Stefano marchesin, Simona Valtrano, Gianziana buttafuoco, Manfredo Atzori und Henning Müller, Multi-Scale Multiple Instance Learning for the Classification of Digital Pathology Images with Global Annotations, in: COMPAY workshop at MICCAI, 2021

Niccolò Marini, Sebastian Otalora, Damian Podareanu, Mart van einthoven, Jeroen van der Laak, Francesco Ciompi, Henning Müller und Manfredo Atzori, Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images (2021), in: Frontiers in Computer Science

Niccolò Marini, Sebastian Otalora, Henning Müller und Manfredo Atzori, 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

Niccolò Marini, Sebastian Otalora, Henning Müller und Manfredo Atzori, 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

Sebastian Otalora, Niccolò Marini, Manfredo Atzori und Henning Müller, 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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