Multichannel Techniques for Motion Artifacts Removal from Electrocardiographic Signals. - Matteo Milanesi; Nicola Martini; Nicola Vanello; Vincenzo Positano; Maria Filomena Santarelli; Rita Paradiso; Danilo De Rossi; Luigi Landini (EMBC, 2006)

Independent component analysis applied to the removal of motion artifacts from electrocardiographic signals. - Matteo Milanesi; Nicola Martini; Nicola Vanello; Vincenzo Positano; Maria Filomena Santarelli; Luigi Landini (Medical Biol. Eng. Comput., 2008)

Evaluation of a pitch estimation algorithm for speech emotion recognition. - Nicola Vanello; Nicola Martini; Matteo Milanesi; H. Keiser; Marcello Calisti; Leonardo Bocchi; Claudia Manfredi; Luigi Landini (MAVEBA, 2009)

The dynamics of EEG gamma responses to unpleasant visual stimuli: From local activity to functional connectivity. - Nicola Martini; Danilo Menicucci; Laura Sebastiani; Remo Bedini; Alessandro Pingitore; Nicola Vanello; Matteo Milanesi; Luigi Landini; Angelo Gemignani (NeuroImage, 2012)

New Methods in Cardiac Magnetic Resonance Imaging and Spectroscopy. - Nicola Martini (2014)

A novel 3D Cartesian random sampling strategy for Compressive Sensing Magnetic Resonance Imaging. - Giuseppe Valvano; Nicola Martini; Maria Filomena Santarelli; Dante Chiappino; Luigi Landini (EMBC, 2015)

An automatic deep learning approach for coronary artery calcium segmentation. - Gianmarco Santini; Daniele Della Latta; Nicola Martini; Giuseppe Valvano; A. Gori; Andrea Ripoli; C. L. Susini; Luigi Landini; Dante Chiappino (CoRR, 2017)

Synthetic contrast enhancement in cardiac CT with Deep Learning. - Gianmarco Santini; Lorena M. Zumbo; Nicola Martini; Gabriele Valvano; Andrea Leo; Andrea Ripoli; Francesco Avogliero; Dante Chiappino; Daniele Della Latta (CoRR, 2018)

Convolutional Neural Networks for the segmentation of microcalcification in Mammography Imaging. - Gabriele Valvano; Gianmarco Santini; Nicola Martini; Andrea Ripoli; Chiara Iacconi; Dante Chiappino; Daniele Della Latta (CoRR, 2018)

Training of a Skull-Stripping Neural Network with efficient data augmentation. - Gabriele Valvano; Nicola Martini; Andrea Leo; Gianmarco Santini; Daniele Della Latta; Emiliano Ricciardi; Dante Chiappino (CoRR, 2018)

Three dimensional MRF obtains highly repeatable and reproducible multi-parametric estimations in the healthy human brain at 1.5T and 3T. - Guido Buonincontri; Jan W. Kurzawski; Joshua D. Kaggie; Tomasz Matys; Ferdia A. Gallagher; Matteo Cencini; Graziella Donatelli; Paolo Cecchi; Mirco Cosottini; Nicola Martini; Francesca Frijia; Domenico Montanaro; et al. (NeuroImage, 2021)

Airborne Radiometric Surveys and Machine Learning Algorithms for Revealing Soil Texture. - Andrea Maino; Matteo Albéri; Emiliano Anceschi; Enrico Chiarelli; Luca Cicala; Tommaso Colonna; Mario De Cesare; Enrico Guastaldi; Nicola Lopane; Fabio Mantovani; Maurizio Marcialis; Nicola Martini; et al. (Remote. Sens., 2022)

Bayesian Convolutional Neural Networks in Medical Imaging Classification: A Promising Solution for Deep Learning Limits in Data Scarcity Scenarios. - Filippo Bargagna; Lisa Anita De Santi; Nicola Martini; Dario Genovesi; Brunella Favilli; Giuseppe Vergaro; Michele Emdin; Assuero Giorgetti; Vincenzo Positano; Maria Filomena Santarelli (J. Digit. Imaging, 2023)

Hardware and Software Setup for Quantitative 23Na Magnetic Resonance Imaging at 3T: A Phantom Study. - Giulio Giovannetti; Alessandra Flori; Nicola Martini; Filippo Cademartiri; Giovanni Aquaro; Alessandro Pingitore; Francesca Frijia (Sensors, 2024)

A Novel Workflow for Electrophysiology Studies in Patients with Brugada Syndrome. - Valentina Hartwig; Maria Sole Morelli; Nicola Martini; Paolo Seghetti; Davide Tirabasso; Vincenzo Positano; Sara Latrofa; Giacomo Mansi; Andrea Rossi 013; Alberto Giannoni; Alessandro Tognetti; Nicola Vanello (Sensors, 2024)