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Simone Mazzetti
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2020 – today
- 2024
- [c15]Sara Colantonio, Andrea Berti, Gianluca Carloni, Claudia Caudai, Giulio Del Corso, Danila Germanese, Eva Pachetti, Maria Antonietta Pascali, Varvara Kalokyri, Haridimos Kondylakis, Charalampos Kalantzopoulos, Nikolaos S. Tachos, Dimitris I. Fotiadis, Valentina Giannini, Simone Mazzetti, Daniele Regge, Nickolas Papanikolaou, Konstantinos Marias, Manolis Tsiknakis:
Data and System Traceability for Transparent AI in Medical Imaging. SEBD 2024: 615-623 - 2022
- [c14]Jovana Panic
, Arianna Defeudis
A fully automatic deep learning algorithm to segment rectal Cancer on MR images: a multi-center study. EMBC 2022: 5066-5069 - [c13]Giovanni Maimone, Giulia Nicoletti
Comparison of Machine and Deep Learning models for automatic segmentation of prostate cancers on multiparametric MRI. MeMeA 2022: 1-5 - 2021
- [c12]Arianna Defeudis
Comparison of radiomics approaches to predict resistance to 1st line chemotherapy in liver metastatic colorectal cancer. EMBC 2021: 3305-3308 - [c11]Davide Barra, Giulia Nicoletti
Deep learning model for automatic prostate segmentation on bicentric T2w images with and without endorectal coil. EMBC 2021: 3370-3373 - [c10]Giulia Nicoletti
Virtual biopsy in prostate cancer: can machine learning distinguish low and high aggressive tumors on MRI? EMBC 2021: 3374-3377 - 2020
- [c9]Valentina Giannini
An innovative radiomics approach to predict response to chemotherapy of liver metastases based on CT images. EMBC 2020: 1339-1342 - [c8]Jovana Panic
A Convolutional Neural Network based system for Colorectal cancer segmentation on MRI images. EMBC 2020: 1675-1678 - [c7]Valentina Giannini
Deep learning to segment liver metastases on CT images: impact on a radiomics method to predict response to chemotherapy. MeMeA 2020: 1-5
2010 – 2019
- 2016
- [j2]Valentina Giannini
MR-T2-weighted signal intensity: a new imaging biomarker of prostate cancer aggressiveness. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 4(3-4): 130-134 (2016) - 2015
- [j1]Valentina Giannini
A fully automatic computer aided diagnosis system for peripheral zone prostate cancer detection using multi-parametric magnetic resonance imaging. Comput. Medical Imaging Graph. 46: 219-226 (2015) - [c6]Francesco Rossi, Alessandro Savino
A 3D Voxel Neighborhood Classification Approach within a Multiparametric MRI Classifier for Prostate Cancer Detection. IWBBIO (1) 2015: 231-239 - [c5]Samanta Rosati
ChiMerge discretization method: Impact on a computer aided diagnosis system for prostate cancer in MRI. MeMeA 2015: 297-302 - 2014
- [c4]Alessandro Savino
A Prostate Cancer Computer Aided Diagnosis Software including Malignancy Tumor Probabilistic Classification. BIOIMAGING 2014: 49-54 - 2013
- [c3]Valentina Giannini
A prostate CAD system based on multiparametric analysis of DCE T1-w, and DW automatically registered images. Computer-Aided Diagnosis 2013: 86703E - 2011
- [c2]Massimo De Luca, Valentina Giannini
A fully automatic method to register the prostate gland on T2-weighted and EPI-DWI images. EMBC 2011: 8029-8032 - [c1]Simone Mazzetti
A CAD system based on multi-parametric analysis for cancer prostate detection on DCE-MRI. Computer-Aided Diagnosis 2011: 79633Q
Coauthor Index
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last updated on 2024-11-28 20:32 CET by the dblp team
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