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2019 Other Open Access OPEN

Le radiazioni
Martinelli M., Bastiani L., Paolicchi F.
Una introduzione alle radiazioni - Materiale per Bright 2019

See at: ISTI Repository Open Access | CNR ExploRA


2019 Contribution to conference Open Access OPEN

Lo Stile di Vita del Frequentatore della Montagna
Martinelli M., Bastiani L., Valoti P., Agazzi G., Carrara B., Parigi G. B., Marina Malannino M., Spinelli A., Calderoli A., Orizio L., Righi M., Pardini F., Benassi A., D'Angelo G., Giardini G., Moroni D., Mrakic Sposta S., Pratali L.
La variazione dei frequentatori della montagna degli ultimi anni sta significativamente cambiando le problematiche del territorio montano: se da un lato aumenta il numero delle presenze temporanee (turisti, lavoratori, etc...), dall'altro diminuisce quello degli abitanti. Il primo, tra le varie, sta elevando il Male Acuto di alta Montagna (MAM) a problema di salute pubblica non trascurabile; il secondo porta ad una minore gestione del territorio generando problemi diretti ed indiretti, tra questi, favorito altresì dal riscaldamento globale, anche la proliferazione delle zecche. Questa ricerca ha esaminato in particolare I fattori di rischio individuale relativo allo stile di vita e al MAM.Source: XXI CONVEGNO NAZIONALE SIMeM, Arabba, 28/09/2019

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2019 Contribution to conference Open Access OPEN

Conoscenza della popolazione sulla radioprotezione e sulla dose radiante delle principali procedure radiologiche
Bastiani L., Salvadori S., Martinelli M., Moroni D., Paolicchi F., Caramella D.
Nel corso degli ultimi decenni stiamo assistendo ad una rapida evoluzione delle tecniche di indagine radiologica, al fine di fornire prestazioni sempre più elevate e performanti. Il frequente e sistematico ricorso alle tecniche di diagnostica per immagini ha fatto sì che queste abbiano assunto il ruolo di strumento indispensabile per definire il corretto percorso terapeutico dei pazienti. Tutte queste metodiche tuttavia, se da un lato aumentano la capacità diagnostica delle procedure, dall'altro possono tendere ad esporre il paziente ad elevate quantità di radiazioni ionizzanti. Spesso il luogo comune associa alla parola "radiazioni" qualcosa di pericoloso. Limitata è però la consapevolezza relativa a quante radiazioni vengono impiegate per le diverse procedure diagnostiche e a quante ciascun individuo è quotidianamente esposto anche a causa del fondo naturale di radiazione.Source: BRIGHT 2019, 27/09/2019

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2019 Other Unknown

Conoscenze Popolazione Radiazioni - Sito del Progetto RadioPoGe
Martinelli M., Bastiani L., Paolicchi F., Salvetti O., Caramella D.
Aggiornamento del Sito web per il progetto "Conoscenze della popolazione sui rischi delle procedure radiologiche" dedicato alla raccolta e alla elaborazione dei dati per la valutazione delle conoscenze della popolazione in merito ai rischi delle procedure radiologiche e alla comprensione delle corrette modalità con cui comunicare tali rischi ai pazienti. Versione 1.3_4 del 2019-12-20

See at: CNR ExploRA | radiazioni.isti.cnr.it


2019 Contribution to conference Open Access OPEN

Male acuto di montagna: una app per test di autovalutazione
Martinelli M., Giardini G., Bastiani L., Agazzi G. C., Mrakic Sposta S., Pratali L.
Una applicazione sul Male Acuto di Montagna per il frequentatore delle montagneSource: XXI CONVEGNO NAZIONALE SIMeM 2019, Arabba, 28/9/2019

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2019 Journal article Open Access OPEN

Estimation of the spatial chromatin structure based on a multiresolution bead-chain model
Caudai C., Salerno E., Zoppe M., Tonazzini A.
We present a method to infer 3D chromatin configurations from Chromosome Conformation Capture data. Quite a few methods have been proposed to estimate the structure of the nuclear DNA in homogeneous populations of cells from this kind of data. Many of them transform contact frequencies into Euclidean distances between pairs of chromatin fragments, and then reconstruct the structure by solving a distance-to-geometry problem. To avoid inconsistencies, our method is based on a score function that does not require any frequency-to-distance translation. We propose a multiscale chromatin model where the chromatin fibre is suitably partitioned at each scale. The partial structures are estimated independently, and connected to rebuild the whole fibre. Our score function consists in a data-fit part and a penalty part, balanced automatically at each scale and each subchain. The penalty part enforces "soft" geometric constraints. As many different structures can fit the data, our sampling strategy produces a set of solutions with similar scores. The procedure contains a few parameters, independent of both the scale and the genomic segment treated. The partition of the fibre, along with intrinsically parallel parts, make this method computationally efficient. Results from human genome data support the biological plausibility of our solutions.Source: IEEE/ACM transactions on computational biology and bioinformatics (Print) 16 (2019): 550–559. doi:10.1109/TCBB.2018.2791439
DOI: 10.1109/tcbb.2018.2791439

See at: ISTI Repository Open Access | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted | CNR ExploRA Restricted | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted


2019 Journal article Open Access OPEN

ChromStruct 4: a Python code to estimate the chromatin structure from Hi-C data
Caudai C., Salerno E., Zoppè M., Merelli I., Tonazzini A.
A method and a stand-alone Python(TM) code to estimate the 3D chromatin structure from chromosome conformation capture data are presented. The method is based on a multiresolution, modified-bead-chain chromatin model, evolved through quaternion operators in a Monte Carlo sampling. The solution space to be sampled is generated by a score function with a data-fit part and a constraint part where the available prior knowledge is implicitly coded. The final solution is a set of 3D configurations that are compatible with both the data and the prior knowledge. The iterative code, provided here as additional material, is equipped with a graphical user interface and stores its results in standard-format files for 3D visualization. We describe the mathematical-computational aspects of the method and explain the details of the code. Some experimental results are reported, with a demonstration of their fit to the data.Source: IEEE/ACM transactions on computational biology and bioinformatics (Online) 16 (2019): 1867–1878. doi:10.1109/TCBB.2018.2838669
DOI: 10.1109/tcbb.2018.2838669

See at: ISTI Repository Open Access | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted | ieeexplore.ieee.org Restricted | CNR ExploRA Restricted | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted


2019 Other Open Access OPEN

Conoscenze Popolazione Radiazioni
Martinelli M., Bastiani L., Paolicchi F.
Sito web per il progetto "Conoscenze della popolazione sui rischi delle procedure radiologiche" dedicato alla raccolta e alla elaborazione dei dati per la valutazione delle conoscenze della popolazione in merito ai rischi delle procedure radiologiche e alla comprensione delle corrette modalità con cui comunicare tali rischi ai pazienti.

See at: ISTI Repository Open Access | CNR ExploRA | radiazioni.isti.cnr.it


2019 Journal article Open Access OPEN

Generalized bayesian model selection for speckle on remote sensing images
Karakus O., Kuruoglu E. E., Altinkaya M. A.
Synthetic aperture radar (SAR) and ultrasound (US) are two important active imaging techniques for remote sensing, both of which are subject to speckle noise caused by coherent summation of back-scattered waves and subsequent nonlinear envelope transformations. Estimating the characteristics of this multiplicative noise is crucial to develop denoising methods and to improve statistical inference from remote sensing images. In this paper, reversible jump Markov chain Monte Carlo (RJMCMC) algorithm has been used with a wider interpretation and a recently proposed RJMCMC-based Bayesian approach, trans-space RJMCMC, has been utilized. The proposed method provides an automatic model class selection mechanism for remote sensing images of SAR and US where the model class space consists of popular envelope distribution families. The proposed method estimates the correct distribution family, as well as the shape and the scale parameters, avoiding performing an exhaustive search. For the experimental analysis, different SAR images of urban, forest and agricultural scenes, and two different US images of a human heart have been used. Simulation results show the efficiency of the proposed method in finding statistical models for speckle.Source: IEEE transactions on image processing 28 (2019): 1748–1758. doi:10.1109/TIP.2018.2878322
DOI: 10.1109/tip.2018.2878322

See at: ISTI Repository Open Access | Explore Bristol Research Open Access | IEEE Transactions on Image Processing Restricted | IEEE Transactions on Image Processing Restricted | IEEE Transactions on Image Processing Restricted | CNR ExploRA Restricted | IEEE Transactions on Image Processing Restricted | IEEE Transactions on Image Processing Restricted | IEEE Transactions on Image Processing Restricted | IEEE Transactions on Image Processing Restricted


2019 Journal article Open Access OPEN

Environmental decision support systems for monitoring small scale oil spills: existing solutions, best practices and current challenges
Moroni D., Pieri G., Tampucci M.
In recent years, large oil spills have received widespread media attention, while small and micro oil spills are usually only acknowledged by the authorities and local citizens who are directly or indirectly affected by these pollution events. However, small oil spills represent the vast majority of oil pollution events. In this paper, multiple oil spill typologies are introduced, and existing frameworks and methods used as best practices for facing them are reviewed and discussed. Specific tools based on information and communication technologies are then presented, considering in particular those which can be used as integrated frameworks for the specific challenges of the environmental monitoring of smaller oil spills. Finally, a prototype case study actually designed and implemented for the management of existing monitoring resources is reported. This case study helps improve the discussion over the actual challenges of early detection and support to the responsible parties and stakeholders in charge of intervention and remediation operations.Source: Journal of marine science and engineering 7 (2019). doi:10.3390/jmse7010019
DOI: 10.3390/jmse7010019
Project(s): ARGOMARINE via OpenAIRE

See at: Journal of Marine Science and Engineering Open Access | Journal of Marine Science and Engineering Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | Journal of Marine Science and Engineering Open Access | www.mdpi.com Open Access | Journal of Marine Science and Engineering Open Access | ZENODO Open Access | Hyper Article en Ligne Restricted | Hyper Article en Ligne Restricted | Hyper Article en Ligne Restricted


2019 Report Open Access OPEN

Developing a Tele-Visit system in ACTIVAGE project
Carboni A.
The work described in this technical note is part of the technological development activities, for the year 2018, related to the H2020 project ACTIVAGE, a European Multi Centric Large Scale Pilot on Smart Living Environments.Source: ISTI Technical reports, 2019
Project(s): ACTIVAGE via OpenAIRE

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2019 Report Closed Access

Deep learning in precision agriculture
Martinelli M., Benassi A., Pardini F., Righi M., Salvetti O., Moroni D.
The work described in this research report is part of the activities carried out within the Scientific Collaboration between the Laboratory of Signals and Images at CNR-ISTI and CNR-IBIMET.Source: Research report, 2019

See at: CNR ExploRA Restricted


2019 Report Closed Access

Deep Learning in Precision Agriculture: prototype 2
Martinelli M., Berton A., Moroni D.
The work described in this research report is part of the activities carried out within the Scientific Collaboration between the Laboratory of Signals and Images at CNR-ISTI and the Institute of Biometeorology (CNR-IBIMET).Source: Research report, 2019

See at: CNR ExploRA Restricted


2019 Other Unknown

Innovazione in telemedicina
Martinelli M.
Seminario sulle tecnologie innovative in telemedicina.

See at: CNR ExploRA


2019 Other Open Access OPEN

La telemedicina sulle montagne italiane il progetto e-Rés@mont
Martinelli M., Pratali L., Giardini G., La Monica D., Bastiani L., Fosson J. P., Bonin S., Cugnetto S., Fiorini A., Pernechele N., Ranfone M., Caligiana L., De La Pierre F., Stella M., Salvetti O., Moroni D.
Presentazione della Serata dedicata al Mal di Montagna e al progetto Europeo Interreg-Alcotra e-Rés@mont, organizzata dal Club Alpino Italiano sezione di Pisa presso il salone storico della Leopolda di Pisa

See at: ISTI Repository Open Access | CNR ExploRA


2019 Doctoral thesis Restricted

Cancer tissue classification from DCE-MRI data using pattern recognition techniques
Venianaki M.
Cancer research has significantly advanced in recent years mainly through developments in medical genomics and bioinformatics. It is expected that such approaches will result in more durable tumour control and fewer side effects compared with conventional treatments such as radiotherapy or chemotherapy. From the imaging standpoint, non-invasive imaging biomarkers (IBs) that assess angiogenic response and tumor environment at an early stage of therapy are of utmost importance, since they could provide useful insights into therapy planning. However, the extraction of IBs is still an open problem, since there are no standardized imaging protocols yet or established methods for the robust extraction of IBs. DCE-MRI is amongst the most promising non-invasive functional imaging modalities while compartmental pharmacokinetic (PK) modelling is the most common technique used for DCE-MRI data analysis. However, PK models suffer from a number of limitations such as modelling complexity, which often leads to variability in the computed biomarkers. To address these problems, alternative DCE-MRI biomarker extraction strategies coupled with a profound understanding of the physiological meaning of IBs is a sine qua non condition. To this end, a more recent model-free approach has been suggested in the literature for DCE-MRI data analysis, which relies on the shape classification of the time-signal uptake curves of image pixels in a selected tumour region of interest. This thesis is centred on this classification approach and the clinical question of whether model-free DCE-MRI data analysis has the potential to provide robust, clinically significant biomarkers using pattern recognition and image analysis techniques.

See at: CNR ExploRA Restricted


2019 Journal article Open Access OPEN

Visible and infrared imaging based inspection of power installation
Jalil B., Pascali M. A., Leone G. R., Martinelli M., Moroni D., Salvetti O., Berton A.
The inspection of power lines is the crucial task for the safe operation of power transmission: its components require regular checking to detect damages and faults that are caused by corrosion or any other environmental agents and mechanical stress. During recent years, the use of Unmanned Autonomous Vehicle (UAV) for environmental and industrial monitoring is constantly growing and the demand for fast and robust algorithms for the analysis of the data acquired by drones during the inspections has increased. In this work, we use UAV to acquire power transmission lines data and apply image processing to highlight expected faults. Our method is based on a fusion algorithm for the infrared and visible power lines images, which is invariant to large scale changes and illumination changes in the real operating environment. Hence, different algorithms from image processing are applied to visible and infrared thermal data, to track the power lines and to detect faults and anomalies. The method significantly identifies edges and hot spots from the set of frames with good accuracy. At the final stage we identify hot spots using thermal images. The paper concludes with the description of the current work, which has been carried out in a research project, namely SCIADRO.Source: Pattern recognition and image analysis 29 (2019): 35–41. doi:10.1134/S1054661819010140
DOI: 10.1134/s1054661819010140

See at: ISTI Repository Open Access | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | Pattern Recognition and Image Analysis Restricted | CNR ExploRA Restricted


2019 Report Restricted

Engine per il riconoscimento delle immagini
Melani A., Coscetti S., Moroni D., Pieri G., Tampucci M., Viani A.
Il presente documento accompagna e descrive i prototipi software realizzati per il riconoscimento delle immagini a corredo del sistema di realtà aumentata per il supporto alla manutenzione e al controllo della linea di trasformazione del progetto IRIDE.Source: Project report, IRIDE, Deliverable D2.2, 2019

See at: CNR ExploRA Restricted


2019 Journal article Open Access OPEN

A new infrared true-color approach for visible-infrared multispectral image analysis
Grifoni E., Campanella B., Legnaioli S., Lorenzetti G., Marras L., Pagnotta S., Palleschi V., Poggialini F., Salerno E., Tonazzini A.
In this article, we present a newmethod for the analysis of visible/Infraredmultispectral sets producing chromatically faithful false-color images, whichmaintain a good readability of the information contained in the non-visible Infrared band. Examples of the application of this technique are given on the multispectral images acquired on the Pietà of Santa Croce of Agnolo Bronzino (1569, Florence) and on the analysis and visualization of the multispectral data obtained on Etruscanmural paintings (Tomb of the Monkey, Siena, Italy, V century B.C.). The fidelity of the chromatic appearance of the resulting images, coupled to the effective visualization of the information contained in the Infrared band, opens interesting perspectives for the use of the method for visualization and presentation of the results of multispectral analysis in Cultural Heritage diffusion, research, and diagnostics.Source: ACM journal on computing and cultural heritage (Print) 12 (2019): 8:1–8:11. doi:10.1145/3241065
DOI: 10.1145/3241065

See at: ISTI Repository Open Access | Journal on Computing and Cultural Heritage Restricted | Journal on Computing and Cultural Heritage Restricted | dl.acm.org Restricted | Journal on Computing and Cultural Heritage Restricted | Journal on Computing and Cultural Heritage Restricted | Journal on Computing and Cultural Heritage Restricted | CNR ExploRA Restricted


2019 Report Closed Access

SCIADRO Algorithms for real-time object detection and recognition
Martinelli M., Benassi A., Salvetti O., Moroni D.
The purpose of this research report is to describe the final prototype implementing algorithms for real-time object detection and recognition.Source: Project report, SCIADRO, 2019

See at: CNR ExploRA Restricted