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Fausto Milletarì
Fausto Milletarì
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Title
Cited by
Cited by
Year
V-net: Fully convolutional neural networks for volumetric medical image segmentation
F Milletari, N Navab, SA Ahmadi
2016 fourth international conference on 3D vision (3DV), 565-571, 2016
113462016
The future of digital health with federated learning
N Rieke, J Hancox, W Li, F Milletari, HR Roth, S Albarqouni, S Bakas, ...
NPJ digital medicine 3 (1), 1-7, 2020
18822020
Privacy-preserving federated brain tumour segmentation
W Li, F Milletarì, D Xu, N Rieke, J Hancox, W Zhu, M Baust, Y Cheng, ...
Machine Learning in Medical Imaging: 10th International Workshop, MLMI 2019 …, 2019
6032019
Hough-CNN: Deep learning for segmentation of deep brain regions in MRI and ultrasound
F Milletari, SA Ahmadi, C Kroll, A Plate, V Rozanski, J Maiostre, J Levin, ...
Computer Vision and Image Understanding 164, 92-102, 2017
4712017
Deep learning of local rgb-d patches for 3d object detection and 6d pose estimation
W Kehl, F Milletari, F Tombari, S Ilic, N Navab
Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016
3432016
Standardized evaluation system for left ventricular segmentation algorithms in 3D echocardiography
O Bernard, JG Bosch, B Heyde, M Alessandrini, D Barbosa, ...
IEEE transactions on medical imaging 35 (4), 967-977, 2015
1132015
Interactive segmentation of medical images through fully convolutional neural networks
T Sakinis, F Milletari, H Roth, P Korfiatis, P Kostandy, K Philbrick, Z Akkus, ...
arXiv preprint arXiv:1903.08205, 2019
1072019
Multimodal image-guided prostate fusion biopsy based on automatic deformable registration
O Zettinig, A Shah, C Hennersperger, M Eiber, C Kroll, H Kübler, T Maurer, ...
International journal of computer assisted radiology and surgery 10, 1997-2007, 2015
922015
Integrating statistical prior knowledge into convolutional neural networks
F Milletari, A Rothberg, J Jia, M Sofka
Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017
622017
Automatic classification of dopamine transporter SPECT: deep convolutional neural networks can be trained to be robust with respect to variable image characteristics
M Wenzel, F Milletari, J Krüger, C Lange, M Schenk, I Apostolova, ...
European journal of nuclear medicine and molecular imaging 46, 2800-2811, 2019
592019
Searching learning strategy with reinforcement learning for 3D medical image segmentation
D Yang, H Roth, Z Xu, F Milletari, L Zhang, D Xu
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
562019
CFCM: segmentation via coarse to fine context memory
F Milletari, N Rieke, M Baust, M Esposito, N Navab
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018
532018
3D intra-operative ultrasound and MR image guidance: pursuing an ultrasound-based management of brainshift to enhance neuronavigation
M Riva, C Hennersperger, F Milletari, A Katouzian, F Pessina, ...
International journal of computer assisted radiology and surgery 12, 1711-1725, 2017
492017
Fully convolutional regression network for accurate detection of measurement points
M Sofka, F Milletari, J Jia, A Rothberg
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2017
382017
Neurreg: Neural registration and its application to image segmentation
W Zhu, A Myronenko, Z Xu, W Li, H Roth, Y Huang, F Milletari, D Xu
Proceedings of the IEEE/CVF winter conference on applications of computer …, 2020
362020
Straight to the point: Reinforcement learning for user guidance in ultrasound
F Milletari, V Birodkar, M Sofka
Smart Ultrasound Imaging and Perinatal, Preterm and Paediatric Image …, 2019
312019
Weakly supervised segmentation from extreme points
H Roth, L Zhang, D Yang, F Milletari, Z Xu, X Wang, D Xu
Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and …, 2019
262019
V-Net: Fully convolutional neural networks for volumetric medical image segmentation. arXiv 2016
F Milletari, N Navab, SA Ahmadi
arXiv preprint arXiv:1606.04797, 0
26
Left Ventricle Segmentation in Cardiac Ultrasound Using Hough-Forests With Implicit Shape and Appearance Priors
SAA Fausto Milletari, Mehmet Yigitsoy, Nassir Navab
MIDAS Journal, 2014
24*2014
Cloud deployment of high-resolution medical image analysis with TOMAAT
F Milletari, J Frei, M Aboulatta, G Vivar, SA Ahmadi
IEEE journal of biomedical and health informatics 23 (3), 969-977, 2018
222018
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