Schlagworte:
- 3D-color-grayscale conversion
- Alzheimer disease
- Alzheimer's disease
- artificial intelligence
- Automatic weak labels
- Biological signal acquisition
- BLS
- Chopped carbon fiber
- Classification
- Clinical decision support
- clustering
- contrastive learning
- Deep convolutional neural network
- Deep Learning
- digital pathology
- EEG
- Electromagnetic interference shielding
- Explainable AI
- Flexible sensor
- Histopathology
- Histopathology image classification
- image retrieval
- interpretability
- Longitudinal clustering
- machine learning
- MOT
- Natural Language Processing
- NIHSS
- Noisy labels
- Open access
- Parkinson's disease
- pathology classification
- Recovery ratio
- retrospective matching network
- Scanning electron microscopy
- self-supervised learning
- SEMG
- ShallowNet
- Stroke
- transformer
- UAV
- whole slide imaging
Publikationen von Manfredo Atzori sortiert nach Zeitschrift und Typ
Medical Image Analysis
| , , , , , , , , , , , und , 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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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , und , The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue (2024), in: Medical Image Analysis |
[DOI] |
| , , und , 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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Medical Informatics Europe 2024
| , , und , An Overview of Public Retinal Optical Coherence Tomography Datasets: Access, Annotations, and Beyond (2024), in: Medical Informatics Europe 2024(1664 - 1668) |
[DOI] |
medRxiv
| , , , , , und , Behavioral Clusters in Ischemic Stroke based on NIHSS Similarity (2023), in: medRxiv(2023--11) |
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Nature Partner Journal on Digital Medicine
| , , , , , , , , , , , , , , , , , , und , 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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Nature Scientific Data
| , , , , , , , , , , , , und , Gaze, visual,myoelectric data of grasps for intelligent prosthetics (2020), in: Nature Scientific Data |
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Neuroscience
| , , , und , 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) |
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Pathology Informatics
| , , , und , Deep learning based retrieval system for gigapixel histopathology cases and open access literature (2019), in: Pathology Informatics |
[DOI] |
| , , , , , , und , Identification and retrieval of prostate cancer cases using a content-based search tool (2019), in: Pathology Informatics |
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PloS one
| , , und , TokenUNet: A new case for transformers integration in efficient and interpretable 3D UNets for brain imaging segmentation (2026), in: PloS one, 21:8(e0354511) |
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Plos One
, , , , und , Comparison of Six Electromyography Acquisition Setups on Hand Movement Classification Tasks (2017), in: Plos One
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PMC
| , , , , , , , , , , , und , Modelling digital health data: The ExaMode ontology for computational pathology (2023), in: PMC |
[DOI] |
Rivista di Chirurgia della mano
| , , und , Elettromiografia, protesica e robotica in rapido progresso verso l'amputazione funzionale: i risultati del progetto Ninapro (2016), in: Rivista di Chirurgia della mano, 53:3 |
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Sci Rep
| , , , , , , und , 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] |
Scientific Data
, und , A large calibrated database of hand movements and grasp kinematics (2020), in: Scientific Data
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| , , , , , , , , und , 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) |
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| , , , , , , , und , Electromyography data for non-invasive naturally controlled robotic hand prostheses (2014), in: Scientific Data, 1:140053 |
[DOI] [URL] |
Scientific Reports
| , , , , und , Improving quality control of whole slide images by explicit artifact augmentation (2024), in: Scientific Reports, 14:1(17847) |
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| , und , Semantic wikis as flexible database interfaces for biomedical applications (2023), in: Scientific Reports, 13:1(1095) |
Sensors
| , , , , und , A multi-scale CNN for transfer learning in sEMG-based hand gesture recognition for prosthetic devices (2024), in: Sensors, 24:22(7147) |
| , , , , und , Questioning Domain Adaptation in Myoelectric Hand Prostheses Control: An Inter-and Intra-Subject Study (2021), in: Sensors, 21:22(7500) |
| , , und , Variability of Muscle Synergies in Hand Grasps: Analysis of Intra-and Inter-Session Data (2020), in: Sensors, 20:15(4297) |
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SENSORS AND ACTUATORS. A, PHYSICAL
| , , , und , A Ni/CCF@PDMS-based flexible and electromagnetic interference-shielding surface electromyography/electrooculography sensor (2026), in: SENSORS AND ACTUATORS. A, PHYSICAL, 400(117530--117530) |
[DOI] |
SIGNAL, IMAGE AND VIDEO PROCESSING
| , , , , , , , und , Improving sEMG signals recognition accuracy using 3D compression and broad learning system (2025), in: SIGNAL, IMAGE AND VIDEO PROCESSING, 19:13 |
[DOI] |
The veterinary journal
| , , , , und , Development of a Deep Convolutional Neural Network to Predict the Grading of Canine Meningiomas from MR images (2018), in: The veterinary journal, 235(90-92) |
Transactions on Neural Systems and Rehabilitation Engineering
, , , , , , , und , Characterization of a Benchmark Database for Myoelectric Movement Classification (2015), in: Transactions on Neural Systems and Rehabilitation Engineering, 23:1(73-83)
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[DOI] [URL] |
Publikationen vom Typ Inbook
2017
| , , , , , , und , Elsevier book on Texture Analysis, Kapitel Analysis of Histopathology Images: From Traditional Machine Learning to Deep Learning, 2017 |
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Publikationen vom Typ Incollection
2026
| , , , , und , Biologically constrained Transformers improve stability and interpretability in single-cell transcriptomics, in: Proceedings of Bioinformatics Italian Society 2026, 2026 |
2015
| , , , , , , , und , Combining Unsupervised Feature Learning and Riesz Wavelets for Histopathology Image Representation: Application to Identifying Anaplastic Medulloblastoma, in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015, Seiten 581-588, Springer International Publishing, 2015 |
[DOI] |
Publikationen vom Typ Inproceedings
2024
| , und , 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] |
| , , , , , , , und , A full pipeline to analyze lung histopathology images, in: Digital and Computational Pathology, SPIE Medical Imaging, 2024 |
[DOI] |
| , , , , , , , , , , und , Automated classification of celiac disease in histopathological images: a multi-scale approach, in: Computer-Aided Diagnosis, SPIE Medical Imaging, 2024 |
[DOI] |
2023
| , , , , , , , und , A dexterous hand prosthesis based on additive manufacturing, in: Proceedings of the Congress of the National Group of Bioengineering (GNB), Patron, 2023 |
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| , , , und , Artifact Augmentation for Learning-based Quality Control of Whole Slide Images, in: EMBC, Sydney, Australia, 2023 |
| , , , , , , , , , und , Intra-operative brain tumor detection with deep learning-optimized hyperspectral imaging, in: Optical Biopsy XXI: Toward Real-Time Spectroscopic Imaging and Diagnosis, SPIE, Seiten 74--92, 2023 |
2022
| , , und , 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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| , , , und , 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
| , , und , Classification of noisy free-text prostate cancer pathology reports using natural language processing, in: Workshop AIDP at ICPR, 2021 |
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| , , , und , 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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| , , , , , , , und , 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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| , , und , 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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2020
| , , , , und , A systematic comparison of deep learning strategies for weakly supervised Gleason grading,, in: SPIE Medical Imaging, Houstonm, TX, USA, 2020 |
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| , , , und , 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 |
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| , , , und , Exploiting the PubMed Central repository to mine out a large multimodal dataset of rare cancer studies, in: SPIE Medical Imaging, Houston, TX, USA, 2020 |
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| , , und , Eye-hand coordination to improve grasp-type recognition in hand prostheses, in: Cybathlon Symposium, Zürich, Switzerland, 2020 |
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| , , und , Generalizing Convolution Neural Networks on Stain Color Heterogeneous Data for Computational Pathology, in: SPIE Medical Imaging, Houston, TX, USA,, 2020 |
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| , , und , 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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| , , , , und , Training a deep neural network for small and highly heterogeneous MRID datasets for cancer grading, in: EMBC Conference, IEEE, 2020 |
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| , , , , und , 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, Seiten 1758--1761, 2020 |
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