Evaluation of compartmental and spectral analysis models of [18F]FDG kinetics for heart and brain studies with PET. - Alessandra Bertoldo; Paolo Vicini; Gianmario Sambuceti; Adriaan A. Lammertsma; Oberdan Parodi; Claudio Cobelli (IEEE Trans. Biomed. Eng., 1998)

Pattern recognition in medical imaging by means of the Hough transform of curves. - Cristina Campi; Annalisa Perasso; Mauro Carlo Beltrametti; Anna Maria Massone; Gianmario Sambuceti; Michele Piana (ISPA, 2013)

Estimate of FDG Excretion by means of Compartmental Analysis and Ant Colony Optimization of Nuclear Medicine Data. - Sara Garbarino; Giacomo Caviglia; Massimo Brignone; Michela Massollo; Gianmario Sambuceti; Michele Piana (Comput. Math. Methods Medicine, 2013)

HT-BONE: a graphical user interface for the identification of bone profiles in CT images via extended Hough transform. - Cristina Campi; Annalisa Perasso; Mauro Carlo Beltrametti; Michele Piana; Gianmario Sambuceti; Anna Maria Massone (Image Processing, 2016)

Predicting the transition from normal aging to Alzheimer's disease: A statistical mechanistic evaluation of FDG-PET data. - Marco Pagani; Alessandro Giuliani; Johanna Öberg; Andrea Chincarini; Silvia Morbelli; Andrea Brugnolo; Dario Arnaldi; Agnese Picco; Matteo Bauckneht; Ambra Buschiazzo; Gianmario Sambuceti; Flavio Nobili (NeuroImage, 2016)

Automated Definition of Skeletal Disease Burden in Metastatic Prostate Carcinoma: a 3D analysis of SPECT/CT images. - Francesco Fiz; Helmut Dittmann; Cristina Campi; Matthias Weissinger; Samine Sahbai; Matthias Reimold; Arnulf Stenzl; Michele Piana; Gianmario Sambuceti; Christian la Fougère (CoRR, 2019)

Prognostic power of the human psoas muscles FDG metabolism in amyotrophic lateral sclerosis. - Rita Lai; Daniela Schenone; Gianmario Sambuceti; Anna Maria Massone; Cristina Campi; Adriano Chiò; Claudia Caponnetto; Angelina Cistaro; Matteo Bauckneht; Vanessa Cossu; Silvia Morbelli; Cecilia Marini; et al. (Computer-Aided Diagnosis, 2020)

Radiomics and artificial intelligence analysis of CT data for the identification of prognostic features in multiple myeloma. - Daniela Schenone; Rita Lai; Michele Cea; Federica Rossi; Lorenzo Torri; Bianca Bignotti; Giulia Succio; Stefano Gualco; Alessio Conte; Alida Dominietto; Anna Maria Massone; Michele Piana; et al. (Computer-Aided Diagnosis, 2020)