Giacomo Tarroni

Enrico Grisan, Giacomo Tarroni, Silvia Visentin, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Human-level CMR image analysis with deep fully convolutional networks pdf

Ben Glocker, Daniel Rueckert, Hideaki Suzuki, 2017, ArXiv.

Anomaly Detection Through Latent Space Restoration Using Vector Quantized Variational Autoencoders pdf

Giacomo Tarroni, Sergio Naval Marimont, G. Tarroni, 2020, 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI).

Automated cardiovascular magnetic resonance image analysis with fully convolutional networks

Ben Glocker, Daniel Rueckert, Bernhard Kainz, 2017, Journal of Cardiovascular Magnetic Resonance.

Deep Generative Model-based Quality Control for Cardiac MRI Segmentation

Daniel Rueckert, Chen Chen, Shuo Wang, 2020, MICCAI.

Automated Segmentation and Non-Rigid Registration for the Quantitative Evaluation of Myocardial Perfusion from Magnetic Resonance Images

Giacomo Tarroni, 2012 .

A fully automated approach to aortic distensibility quantification from fetal ultrasound images

Enrico Grisan, Giacomo Tarroni, Silvia Visentin, 2015, 2015 Computing in Cardiology Conference (CinC).

Respiratory motion correction for 2D cine cardiac MR images using probabilistic edge maps

Daniel Rueckert, Declan P. O'Regan, Wenjia Bai, 2016, 2016 Computing in Cardiology Conference (CinC).

Deep Learning for Cardiac Image Segmentation: A Review

Daniel Rueckert, Chen Qin, Huaqi Qiu, 2020, Frontiers in Cardiovascular Medicine.

Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction

Daniel Rueckert, Chen Chen, Yike Guo, 2019, MICCAI.

Learning-Based Quality Control for Cardiac MR Images

Ben Glocker, Daniel Rueckert, Paul M. Matthews, 2018, IEEE Transactions on Medical Imaging.

Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation pdf

Daniel Rueckert, Chen Chen, Wenjia Bai, 2019, STACOM@MICCAI.

Blissful Ignorance: Anti-Transfer Learning for Task Invariance pdf

Tillman Weyde, Eric Guizzo, Giacomo Tarroni, 2020, ArXiv.

A novel approach to aortic intima-media thickness quantification from fetal ultrasound images

Enrico Grisan, Giacomo Tarroni, Silvia Visentin, 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).

A Comprehensive Approach for Learning-Based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks

Daniel Rueckert, Declan P. O'Regan, Wenjia Bai, 2018, MICCAI.

Near-automated quantification of prenatal aortic intima-media thickness from ultrasound images

Enrico Grisan, Giacomo Tarroni, Silvia Visentin, 2014, Computing in Cardiology 2014.

Anti-Transfer Learning for Task Invariance in Convolutional Neural Networks for Speech Processing

Tillman Weyde, Eric Guizzo, Giacomo Tarroni, 2020 .

A supervised learning approach for the robust detection of heart beat in plethysmographic data

Michele Rossi, Enrico Grisan, Seung Keun Yoon, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Semi-supervised Learning for Network-Based Cardiac MR Image Segmentation

Ben Glocker, Daniel Rueckert, Hideaki Suzuki, 2017, MICCAI.

Near-automated 3D segmentation of left and right ventricles on magnetic resonance images

Cristiana Corsi, Claudio Lamberti, Giacomo Tarroni, 2013, 2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA).

Semiautomatic detection of villi in confocal endoscopy for the evaluation of celiac disease

Davide Boschetto, Hadis Mirzaei, Rupert Leong, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Anti-transfer learning for task invariance in convolutional neural networks for speech processing

Tillman Weyde, Giacomo Tarroni, Eric Guizzo, 2021, Neural Networks.

Implicit field learning for unsupervised anomaly detection in medical images

Giacomo Tarroni, Sergio Naval Marimont, G. Tarroni, 2021, MICCAI.

Enhancing MR Image Segmentation with Realistic Adversarial Data Augmentation pdf

Daniel Rueckert, Chen Qin, Wenjia Bai, 2021, ArXiv.

A population-based phenome-wide association study of cardiac and aortic structure and function

Yike Guo, Daniel Rueckert, Florian Guitton, 2020, Nature Medicine.

Myocardial perfusion: near-automated evaluation from contrast-enhanced MR images obtained at rest and during vasodilator stress.

Victor Mor-Avi, Cristiana Corsi, Amit R. Patel, 2012, Radiology.