Fausto Milletarì

Chan Zuckerberg Initiative (United States) — United States

Computer Science · Physical Sciences

20h-index3.4kcitations53works2.02yr avg
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Research Topics

Medical Image Segmentation Techniques(22), Advanced Neural Network Applications(18), Radiomics and Machine Learning in Medical Imaging(11), Medical Imaging and Analysis(11), AI in cancer detection(10)

Publications53 total

rbio1 - training scientific reasoning LLMs with biological world models as soft verifiers
2025· 2 citedOpen Access
Adapting Self-Supervised Learning for Computational Pathology
arXiv (Cornell University)·2024· 2 citedOpen Access
Towards an AI-based assessment model of surgical difficulty during early phase laparoscopic cholecystectomy
Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization·2023· 8 citedOpen Access
Towards accurate surgical workflow recognition with convolutional networks and transformers
Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization·2021· 25 cited
Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation
arXiv (Cornell University)·2020Open Access
NeurReg: Neural Registration and Its Application to Image Segmentation
2020· 33 cited
Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning
Lecture notes in computer science·2020· 54 cited
NeurReg: Neural Registration and Its Application to Image Segmentation
arXiv (Cornell University)·2019· 4 citedOpen Access
Privacy-preserving Federated Brain Tumour Segmentation
arXiv (Cornell University)·2019· 63 citedOpen Access
Automatic classification of dopamine transporter SPECT: deep convolutional neural networks can be trained to be robust with respect to variable image characteristics
European Journal of Nuclear Medicine and Molecular Imaging·2019· 65 cited
Correlation via synthesis: end-to-end nodule image generation and radiogenomic map learning based on generative adversarial network
arXiv (Cornell University)·2019· 1 citedOpen Access
Correlation via synthesis: end-to-end nodule image generation and\n radiogenomic map learning based on generative adversarial network
arXiv (Cornell University)·2019· 11 citedOpen Access
Interactive segmentation of medical images through fully convolutional neural networks
arXiv (Cornell University)·2019· 60 citedOpen Access
Improving V-Nets for multi-class abdominal organ segmentation
2019· 7 cited
Straight to the point: reinforcement learning for user guidance in\n ultrasound
arXiv (Cornell University)·2019Open Access
Influence of group normalization in multi-class organ segmentation of abdominal CT volumes
IEICE Technical Report; IEICE Tech. Rep.·2019
Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation
Lecture notes in computer science·2019· 51 cited
Privacy-Preserving Federated Brain Tumour Segmentation
Lecture notes in computer science·2019· 490 citedOpen Access
Straight to the Point: Reinforcement Learning for User Guidance in Ultrasound
Lecture notes in computer science·2019· 4 citedOpen Access
Tunable CT Lung Nodule Synthesis Conditioned on Background Image and Semantic Features
Lecture notes in computer science·2019· 14 cited
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Frequent Co-authors

Nassir Navab(22), Seyed‐Ahmad Ahmadi(13), Daguang Xu(11), Ziyue Xu(11), Holger R. Roth(11), Nicola Rieke(6), Annika Plate(6), Wenqi Li(5), M. Jorge Cardoso(5), Christine Kroll(5), Kai Bötzel(5), Dong Yang(5), Michal Sofka(4), Xiaosong Wang(4), Pascal Fallavollita(4), Maximilian Baust(3), Verena Rozanski(3), Juliana Maiostre(3), Johannes Levin(3), Olaf Dietrich(3)