Palavras-chave:
Publicações de Manfredo Atzori
2024
| , and , A comparative study of deep convolutional neural networks for the analysis of retinal damage in optical coherence tomography, in: Imaging Informatics for Healthcare, Research, and Applications, 2024 |
[DOI] |
| , , , , , , , and , A full pipeline to analyze lung histopathology images, in: Digital and Computational Pathology, SPIE Medical Imaging, 2024 |
[DOI] |
| , , , , , and , A systematic comparison of deep learning methods for Gleason grading and scoring (2024), in: Medical Image Analysis |
[DOI] |
| , , and , An Overview of Public Retinal Optical Coherence Tomography Datasets: Access, Annotations, and Beyond (2024), in: Medical Informatics Europe 2024(1664 - 1668) |
[DOI] |
| , , , , , , , , , , and , Automated classification of celiac disease in histopathological images: a multi-scale approach, in: Computer-Aided Diagnosis, SPIE Medical Imaging, 2024 |
[DOI] |
| , , , , , and , Exploring Publicly Accessible Optical Coherence Tomography Datasets: A Comprehensive Overview (2024), in: MDPI Diagostics |
[DOI] |
| , , , , , , , , , , , and , Multimodal Representations of Biomedical Knowledge from Limited Training Whole Slide Images and Reports using Deep Learning (2024), in: Medical Image Analysis |
[DOI] |
| , , and , 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] |
| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue (2024), in: Medical Image Analysis |
[DOI] |
2023
| , , , , , , , and , A dexterous hand prosthesis based on additive manufacturing, in: Proceedings of the Congress of the National Group of Bioengineering (GNB), Patron, 2023 |
|
| , , , and , Artifact Augmentation for Learning-based Quality Control of Whole Slide Images, in: EMBC, Sydney, Australia, 2023 |
| , , , , and , Functional Synergies Applied to a Publicly Available Dataset of Hand Grasps Show Evidence of Kinematic-Muscular Synergistic Control (2023), in: IEEE Access, Volume 11(108544 - 108560) |
[DOI] |
| , , , , , , and , Improving the classification of veterinary thoracic radiographs through inter-species and inter-pathology self-supervised pre-training of deep learning models (2023), in: Sci Rep:Article number: 19518 (2023) |
[DOI] |
| , , , , , , , , , , , and , Modelling digital health data: The ExaMode ontology for computational pathology (2023), in: PMC |
[DOI] |
| , , , , , , , , , and , Modelling digital health data: The ExaMode ontology for computational pathology (2023), in: Journal of Pathology Informatics(100332) |
| , and , Semantic wikis as flexible database interfaces for biomedical applications (2023), in: Scientific Reports, 13:1(1095) |
| , , , and , Spatial and temporal muscle synergies provide a dual characterization of low-dimensional and intermittent control of upper-limb movements (2023), in: Neuroscience, 514(100--122) |
|
2022
| , , and , 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 |
|
| , , , , , , , , , , , , and , Empowering Digital Pathology Applications through Explainable Knowledge Extraction Tools (2022), in: Journal of Digital Pathology |
|
| , , , , and , Evaluation of methods for the extraction spatial muscle synergies (2022), in: Frontiers in neuroscience |
|
| , , and , Improving Robotic Hand Prosthesis Control With Eye Tracking and Computer Vision: A Multimodal Approach Based on the Visuomotor Behavior of Grasping (2022), in: Frontiers in Artificial Intelligence(199) |
|
| , , and , Mapping of the Upper Limb Work-Space: Benchmarking Four Wrist Smoothness Metrics (2022), in: Applied Sciences, 12:24(12643) |
| , , , , , , and , stainlib: a python library for augmentation and normalization of histopathology H&E images (2022), in: bioArXiv |
|
| , , , , , , , , , , , , , , , , , , and , Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations (2022), in: Nature Partner Journal on Digital Medicine |
|
| , , , and , 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 |
|
2021
| , , and , Classification of noisy free-text prostate cancer pathology reports using natural language processing, in: Workshop AIDP at ICPR, 2021 |
|
| , , and , Combining weak and strong supervised learning improves strong supervision in Gleason pattern classification (2021), in: BMC Medical Imaging |
|
| , , , and , 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 |
|
| , , , , , , , and , Multi-Scale Multiple Instance Learning for the Classification of Digital Pathology Images with Global Annotations, in: COMPAY workshop at MICCAI, 2021 |
|
| , , , , , , and , Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images (2021), in: Frontiers in Computer Science |
|
| , , , , and , Questioning Domain Adaptation in Myoelectric Hand Prostheses Control: An Inter-and Intra-Subject Study (2021), in: Sensors, 21:22(7500) |
| , , and , 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 |
|
| , , and , 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 |
|
2020
, and , A large calibrated database of hand movements and grasp kinematics (2020), in: Scientific Data
|
|
| , , , , and , A systematic comparison of deep learning strategies for weakly supervised Gleason grading,, in: SPIE Medical Imaging, Houstonm, TX, USA, 2020 |
|
| , and , Availability of sEMG controlled prosthetic arm components, Information Systems Institute, HES-SO Valais; EPFL, 2020 |
|
| , , , and , Effect of movement type on the classification of electromyography data for the control of dexterous prosthetic hands, in: Biorob, International Conference on Biomedical Robotics & Biomechatronics, New York City, NY, USA, 2020 |
|
| , , , and , Exploiting the PubMed Central repository to mine out a large multimodal dataset of rare cancer studies, in: SPIE Medical Imaging, Houston, TX, USA, 2020 |
|
| , , and , Eye-hand coordination to improve grasp-type recognition in hand prostheses, in: Cybathlon Symposium, Zürich, Switzerland, 2020 |
|
| , , , , , , , , and , Gaze, behavioral, and clinical data for phantom limbs after hand amputation from 15 amputees and 29 controls (2020), in: Scientific Data, 7:1(1--14) |
|
| , , , , , , , , , , , , and , Gaze, visual,myoelectric data of grasps for intelligent prosthetics (2020), in: Nature Scientific Data |
|
| , , and , Generalizing Convolution Neural Networks on Stain Color Heterogeneous Data for Computational Pathology, in: SPIE Medical Imaging, Houston, TX, USA,, 2020 |
|
| , , and , Semi-Weakly Supervised Learning for Prostate Cancer Image Classification with Teacher-Student Deep Convolutional Networks, in: MICCAI workshop Labels, Lima, Peru, 2020 |
|
| , , , , and , Training a deep neural network for small and highly heterogeneous MRID datasets for cancer grading, in: EMBC Conference, IEEE, 2020 |
|
| , , , , and , Training Deep Neural Networks for Small and Highly Heterogeneous MRI Datasets for Cancer Grading, in: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC), IEEE, páginas 1758--1761, 2020 |
|
| , , , , and , Using Publicly Available Medical Images from the Open Access Literature and Social Networks for Model Training and Knowledge Extraction, in: Multimedia Modeling (MMM 2020), Seoul, Korea, 2020 |
|
| , , and , Variability of Muscle Synergies in Hand Grasps: Analysis of Intra-and Inter-Session Data (2020), in: Sensors, 20:15(4297) |
|
2019
, , , , and , A Quantitative Taxonomy of Human Hand Grasps, (2019), in: Journal of NeuroEngineering and Rehabilitation,, 16:28
|
|
| , , , and , An Augmented Reality Environment to Provide Visual Feedback to Amputees during sEMG Data Acquisitions, in: TAROS (Towards Autonomous Robotic Systems), London, United Kingdom, 2019 |
|
| , , , and , Analyzing the trade-off between training session time and performance in myoelectric hand gesture recognition during upper limb movement, in: 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR), Toronto, Canada, 2019 |
|