The integration of artificial intelligence (AI) into medical imaging has guided an era of transformation in healthcare. This paper presents the research activities that a multidisciplinary research group within the Signals and Images Lab of the Institute of Information Science and Technologies of the National Research Council of Italy is carrying out to explore the great potential of AI in medical imaging. From the convolutional neural network-based segmentation of Covid-19 lung patterns to the radiomic signature for benign/malignant breast nodule discrimination, to the automatic grading of prostate cancer, this work highlights the paradigm shift that AI has brought to medical imaging, revolutionizing diagnosis and patient care.

From Covid-19 detection to cancer grading: how medical-AI is boosting clinical diagnostics and may improve treatment

Berti A.;Buongiorno R.;Carloni G.;Caudai C.;Conti F.;Del Corso G.;Germanese D.;Moroni D.;Pachetti E.;Pascali M. A.;Colantonio S.
2024

Abstract

The integration of artificial intelligence (AI) into medical imaging has guided an era of transformation in healthcare. This paper presents the research activities that a multidisciplinary research group within the Signals and Images Lab of the Institute of Information Science and Technologies of the National Research Council of Italy is carrying out to explore the great potential of AI in medical imaging. From the convolutional neural network-based segmentation of Covid-19 lung patterns to the radiomic signature for benign/malignant breast nodule discrimination, to the automatic grading of prostate cancer, this work highlights the paradigm shift that AI has brought to medical imaging, revolutionizing diagnosis and patient care.
2024
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Trustworthy AI
Visual intelligence
Medical imaging
Radiomics
Convolutional Neural Networks
Deep Neural Networks
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Descrizione: From Covid-19 detection to cancer grading: how medical-AI is boosting clinical diagnostics and may improve treatment
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/511632
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