Maria A Pascali | Consiglio Nazionale delle Ricerche (CNR) (original) (raw)

Papers by Maria A Pascali

Research paper thumbnail of Exploring the potential and challenges of AI in clinical diagnostics and remote assistance of individuals

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Alzheimer Disease Detection from Raman Spectroscopy of the Cerebrospinal Fluid via Topological Machine Learning

AITA 2023

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Branched covers of the sphere and the prime-degree conjecture

arXiv (Cornell University), Oct 14, 2010

Bookmarks Related papers MentionsView impact

Research paper thumbnail of ViDA 3D: Towards a View-based Dataset for Aesthetic prediction on 3D models

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Exploring UAVs for Structural Health Monitoring

HAL (Le Centre pour la Communication Scientifique Directe), Jun 16, 2022

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Surface branched covers and geometric 2-orbifolds

arXiv (Cornell University), Sep 13, 2007

Bookmarks Related papers MentionsView impact

Research paper thumbnail of A seamless pipeline for the acquisition of the body shape: the Virtuoso case study

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Architectural Heritage: 3D Documentation and Structural Monitoring Using UAV

Bookmarks Related papers MentionsView impact

Research paper thumbnail of A Topological Machine Learning Pipeline for Classification

Mathematics, Aug 27, 2022

Bookmarks Related papers MentionsView impact

Research paper thumbnail of A preliminary study for a marker-based crack monitoring in ancient structures

Proceedings of the 2nd International Conference on Applications of Intelligent Systems

Historical buildings are undeniably valuable documents of the history of the world. Their preserv... more Historical buildings are undeniably valuable documents of the history of the world. Their preservation has attracted considerable attention among modern societies, being a major issues both from economical and cultural point of view. This paper describes how image processing and marker-based application may support the long-term monitoring of crack patterns in the context of cultural heritage preservation, with a special focus on ancient structures. In detail, this work includes a state of the art about the most used techniques in structural monitoring, a description of the proposed methodology and the experimentation details. A discussion about the results and future works concludes the paper.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of On the Effectiveness of 3D Vision Transformers for the Prediction of Prostate Cancer Aggressiveness

Lecture Notes in Computer Science, 2022

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Cardio-metabolic risk modeling and assessment through sensor-based measurements

International Journal of Medical Informatics

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Signal Processing for Underwater Archaeology

Proceedings of the 5th International Workshop on Image Mining. Theory and Applications, 2015

Bookmarks Related papers MentionsView impact

Research paper thumbnail of May Radiomic Data Predict Prostate Cancer Aggressiveness?

Radiomics can quantify tumor phenotypic characteristics non-invasively by defining a signature co... more Radiomics can quantify tumor phenotypic characteristics non-invasively by defining a signature correlated with biological information. Thanks to algorithms derived from computer vision to extract features from images, and machine learning methods to mine data, Radiomics is the perfect case study of application of Artificial Intelligence in the context of precision medicine. In this study we investigated the association between radiomic features extracted from multi-parametric magnetic resonance imaging (mp-MRI)of prostate cancer (PCa) and the tumor histologic subtypes (using Gleason Score) using machine learning algorithms, in order to identify which of the mp-MRI derived radiomic features can distinguish high and low risk PCa.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of UAVs and UAV Swarms for Civilian Applications: Communications and Image Processing in the SCIADRO Project

Wireless and Satellite Systems, 2018

Bookmarks Related papers MentionsView impact

Research paper thumbnail of On Some Scientific Results of the ICPR-2020

Pattern Recognition and Image Analysis, 2021

This special issue of PRIA is devoted to some scientific results and trends of the 25th Internati... more This special issue of PRIA is devoted to some scientific results and trends of the 25th International Conference on Pattern Recognition (Virtual, Milano, Italy, January 10–15, 2021). Two important events of ICPR-2020 are represented in this special issue: (1) The paper of Professor Ching Yee Suen (Centre for Pattern Recognition and Machine Intelligence, Department of Computer Science and Software Engineering, Concordia University, Montreal, QC, Canada)–the recent winner of IAPR very prestigious K.S. Fu Prize for a year of 2020. The paper based on his lecture “From handwriting to human personality and facial beauty” presented at the ICPR 2020; (2) Special issue “ICPR-2020 Workshop “Image Mining. Theory and Applications.” The analysis of the scientific contribution of IMTA-VII-2021 allows us to draw the following conclusions: (1) The construction of a unified mathematical theory of image analysis is still far from complete. (2) There is considerable interest in the development of new mathematical methods for analyzing and evaluating information presented in the form of images. (3) There is a tendency to expand the mathematical apparatus in the development of new methods of image analysis and recognition by involving in this process areas of mathematics that were not previously used in image analysis. (4) The gap between the capabilities of new mathematical methods of image analysis and recognition and their actual use in solving applied problems remains significant. (5) There is an excessive use of neural networks in solving applied problems of image analysis and image recognition, and quite often without proper justification and interpretation of the results. The special issue includes articles based on the workshop papers selected by the IMTA-VII-2021 Program Committee for publication in PRIA. The PRIA special issue “Scientific Resume of the 25th International Conference on Pattern Recognition” is prepared by the National Committee for Pattern Recognition and Image Analysis of the Russian Academy of Sciences, the IAPR member society, and by the IAPR Technical Committee no. 16 on Algebraic and Discrete Mathematical Techniques in Pattern Recognition and Image Analysis.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Virtual Immersive Environments for Underwater Archaeological Exploration

Proceedings of the 5th International Workshop on Image Mining. Theory and Applications, 2015

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Virtual environment as a tool to access the marine abysses

OCEANS 2015 - Genova, 2015

This paper describes a virtual environment designed and developed aiming at increasing the fruiti... more This paper describes a virtual environment designed and developed aiming at increasing the fruition of underwater exploration. Such system is under development in the frame of ARROWS project (end August 2015, funded by the European Commission). Main objectives of ARROWS project are the development and integration of advanced technologies and tools for mapping, diagnosing, cleaning, and securing underwater and coastal archaeological sites. Along with it, an informative system, that has the role to make easier the management of the heterogeneous set of data available (such as archival and historical data; georeferenced images, sonograms, videos; texture and shape of artefacts; others), is in development. The virtual environment aims at representing all the available data in a 3D interactive and informative scene. In this way, the archaeological site is accessible both to experts (for research purposes, e.g. classification of artefacts by template matching) and to the general public (for dissemination of the underwater cultural heritage). Due to the high educational value of this system, it has been enriched by dedicated functionalities for the management and representation of biological information, which was beyond the original project scopes.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Radiomics to Predict Prostate CancerAggressiveness: A Preliminary Study

2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE), 2019

Radiomics is encouraging a paradigm shift in oncological diagnostics towards the symbiosis of rad... more Radiomics is encouraging a paradigm shift in oncological diagnostics towards the symbiosis of radiology and Artificial Intelligence (AI) techniques. The aim is to exploit very accurate, robust image processing algorithms and provide quantitative information about the phenotypic differences of cancer traits. By exploring the association between this quantitative information and patients’ prognosis, AI algorithms are boosting the power of radiomics in the perspective of precision oncology. However,thechoiceofthemostsuitableAImethodcandetermine the success of a radiomic application. The current state-of-the art methods in radiomics aim at extracting statistical features from biomedical images and, then, process them with Machine Learning (ML) techniques. Many works have been reported in the literature presenting various combinations of radiomic features and ML methods. In this preliminary study, we aim to analyse the performance of a radiomic approach to predict prostate cancer (PCa) aggressivenessfrommulti-parametricMagneticResonanceImaging (mp-MRI). Clinical mp-MRI data were collected from patients with histology-confirmed PCa and labelled by a team of expert radiologists. Such data were used to extract and select two sets of radiomic features; hence, the classification performances of five classifiers were assessed. This analysis is meant as a preliminary step towards the overall goal of investigating the potential of radiomic-based analyses.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Augmented reality, artificial intelligence and machine learning in Industry 4.0: case studies at SI-Lab

Zenodo (CERN European Organization for Nuclear Research), Feb 10, 2022

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Exploring the potential and challenges of AI in clinical diagnostics and remote assistance of individuals

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Alzheimer Disease Detection from Raman Spectroscopy of the Cerebrospinal Fluid via Topological Machine Learning

AITA 2023

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Branched covers of the sphere and the prime-degree conjecture

arXiv (Cornell University), Oct 14, 2010

Bookmarks Related papers MentionsView impact

Research paper thumbnail of ViDA 3D: Towards a View-based Dataset for Aesthetic prediction on 3D models

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Exploring UAVs for Structural Health Monitoring

HAL (Le Centre pour la Communication Scientifique Directe), Jun 16, 2022

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Surface branched covers and geometric 2-orbifolds

arXiv (Cornell University), Sep 13, 2007

Bookmarks Related papers MentionsView impact

Research paper thumbnail of A seamless pipeline for the acquisition of the body shape: the Virtuoso case study

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Architectural Heritage: 3D Documentation and Structural Monitoring Using UAV

Bookmarks Related papers MentionsView impact

Research paper thumbnail of A Topological Machine Learning Pipeline for Classification

Mathematics, Aug 27, 2022

Bookmarks Related papers MentionsView impact

Research paper thumbnail of A preliminary study for a marker-based crack monitoring in ancient structures

Proceedings of the 2nd International Conference on Applications of Intelligent Systems

Historical buildings are undeniably valuable documents of the history of the world. Their preserv... more Historical buildings are undeniably valuable documents of the history of the world. Their preservation has attracted considerable attention among modern societies, being a major issues both from economical and cultural point of view. This paper describes how image processing and marker-based application may support the long-term monitoring of crack patterns in the context of cultural heritage preservation, with a special focus on ancient structures. In detail, this work includes a state of the art about the most used techniques in structural monitoring, a description of the proposed methodology and the experimentation details. A discussion about the results and future works concludes the paper.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of On the Effectiveness of 3D Vision Transformers for the Prediction of Prostate Cancer Aggressiveness

Lecture Notes in Computer Science, 2022

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Cardio-metabolic risk modeling and assessment through sensor-based measurements

International Journal of Medical Informatics

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Signal Processing for Underwater Archaeology

Proceedings of the 5th International Workshop on Image Mining. Theory and Applications, 2015

Bookmarks Related papers MentionsView impact

Research paper thumbnail of May Radiomic Data Predict Prostate Cancer Aggressiveness?

Radiomics can quantify tumor phenotypic characteristics non-invasively by defining a signature co... more Radiomics can quantify tumor phenotypic characteristics non-invasively by defining a signature correlated with biological information. Thanks to algorithms derived from computer vision to extract features from images, and machine learning methods to mine data, Radiomics is the perfect case study of application of Artificial Intelligence in the context of precision medicine. In this study we investigated the association between radiomic features extracted from multi-parametric magnetic resonance imaging (mp-MRI)of prostate cancer (PCa) and the tumor histologic subtypes (using Gleason Score) using machine learning algorithms, in order to identify which of the mp-MRI derived radiomic features can distinguish high and low risk PCa.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of UAVs and UAV Swarms for Civilian Applications: Communications and Image Processing in the SCIADRO Project

Wireless and Satellite Systems, 2018

Bookmarks Related papers MentionsView impact

Research paper thumbnail of On Some Scientific Results of the ICPR-2020

Pattern Recognition and Image Analysis, 2021

This special issue of PRIA is devoted to some scientific results and trends of the 25th Internati... more This special issue of PRIA is devoted to some scientific results and trends of the 25th International Conference on Pattern Recognition (Virtual, Milano, Italy, January 10–15, 2021). Two important events of ICPR-2020 are represented in this special issue: (1) The paper of Professor Ching Yee Suen (Centre for Pattern Recognition and Machine Intelligence, Department of Computer Science and Software Engineering, Concordia University, Montreal, QC, Canada)–the recent winner of IAPR very prestigious K.S. Fu Prize for a year of 2020. The paper based on his lecture “From handwriting to human personality and facial beauty” presented at the ICPR 2020; (2) Special issue “ICPR-2020 Workshop “Image Mining. Theory and Applications.” The analysis of the scientific contribution of IMTA-VII-2021 allows us to draw the following conclusions: (1) The construction of a unified mathematical theory of image analysis is still far from complete. (2) There is considerable interest in the development of new mathematical methods for analyzing and evaluating information presented in the form of images. (3) There is a tendency to expand the mathematical apparatus in the development of new methods of image analysis and recognition by involving in this process areas of mathematics that were not previously used in image analysis. (4) The gap between the capabilities of new mathematical methods of image analysis and recognition and their actual use in solving applied problems remains significant. (5) There is an excessive use of neural networks in solving applied problems of image analysis and image recognition, and quite often without proper justification and interpretation of the results. The special issue includes articles based on the workshop papers selected by the IMTA-VII-2021 Program Committee for publication in PRIA. The PRIA special issue “Scientific Resume of the 25th International Conference on Pattern Recognition” is prepared by the National Committee for Pattern Recognition and Image Analysis of the Russian Academy of Sciences, the IAPR member society, and by the IAPR Technical Committee no. 16 on Algebraic and Discrete Mathematical Techniques in Pattern Recognition and Image Analysis.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Virtual Immersive Environments for Underwater Archaeological Exploration

Proceedings of the 5th International Workshop on Image Mining. Theory and Applications, 2015

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Virtual environment as a tool to access the marine abysses

OCEANS 2015 - Genova, 2015

This paper describes a virtual environment designed and developed aiming at increasing the fruiti... more This paper describes a virtual environment designed and developed aiming at increasing the fruition of underwater exploration. Such system is under development in the frame of ARROWS project (end August 2015, funded by the European Commission). Main objectives of ARROWS project are the development and integration of advanced technologies and tools for mapping, diagnosing, cleaning, and securing underwater and coastal archaeological sites. Along with it, an informative system, that has the role to make easier the management of the heterogeneous set of data available (such as archival and historical data; georeferenced images, sonograms, videos; texture and shape of artefacts; others), is in development. The virtual environment aims at representing all the available data in a 3D interactive and informative scene. In this way, the archaeological site is accessible both to experts (for research purposes, e.g. classification of artefacts by template matching) and to the general public (for dissemination of the underwater cultural heritage). Due to the high educational value of this system, it has been enriched by dedicated functionalities for the management and representation of biological information, which was beyond the original project scopes.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Radiomics to Predict Prostate CancerAggressiveness: A Preliminary Study

2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE), 2019

Radiomics is encouraging a paradigm shift in oncological diagnostics towards the symbiosis of rad... more Radiomics is encouraging a paradigm shift in oncological diagnostics towards the symbiosis of radiology and Artificial Intelligence (AI) techniques. The aim is to exploit very accurate, robust image processing algorithms and provide quantitative information about the phenotypic differences of cancer traits. By exploring the association between this quantitative information and patients’ prognosis, AI algorithms are boosting the power of radiomics in the perspective of precision oncology. However,thechoiceofthemostsuitableAImethodcandetermine the success of a radiomic application. The current state-of-the art methods in radiomics aim at extracting statistical features from biomedical images and, then, process them with Machine Learning (ML) techniques. Many works have been reported in the literature presenting various combinations of radiomic features and ML methods. In this preliminary study, we aim to analyse the performance of a radiomic approach to predict prostate cancer (PCa) aggressivenessfrommulti-parametricMagneticResonanceImaging (mp-MRI). Clinical mp-MRI data were collected from patients with histology-confirmed PCa and labelled by a team of expert radiologists. Such data were used to extract and select two sets of radiomic features; hence, the classification performances of five classifiers were assessed. This analysis is meant as a preliminary step towards the overall goal of investigating the potential of radiomic-based analyses.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Augmented reality, artificial intelligence and machine learning in Industry 4.0: case studies at SI-Lab

Zenodo (CERN European Organization for Nuclear Research), Feb 10, 2022

Bookmarks Related papers MentionsView impact