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Your search keyword '"Conforto, S."' showing total 9 results
Start Over Author "Conforto, S." Publisher springer international publishing
9 results on '"Conforto, S."'

3. Attentional Focus and Functional Connectivity in Cycling: An EEG Case Study

Author

Comani, S., Di Fronso, S., Filho, E., Castronovo, A. M., Schmid, M., Bortoli, L., Conforto, S., Robazza, C., Bertollo, M., Magjarevic, Ratko, Editor-in-chief, Ładyzynsk, Piotr, Series editor, Ibrahim, Fatimah, Series editor, Lacković, Igor, Series editor, Rock, Emilio Sacristan, Series editor, and Roa Romero, Laura M., editor

Published
2014
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5. EMG and Kinematics Assessment of Postural Responses during Balance Perturbation on a 3D Robotic Platform: Preliminary Results in Children with Hemiplegia

Author

De Marchis, C., Patané, F., Petrarca, M., Carniel, S., Schmid, M., Conforto, S., Castelli, E., Cappa, P., D’Alessio, T., Magjarevic, Ratko, Editor-in-chief, Ładyzynsk, Piotr, Series editor, Ibrahim, Fatimah, Series editor, Lacković, Igor, Series editor, Rock, Emilio Sacristan, Series editor, and Roa Romero, Laura M., editor

Published
2014
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8. Small and Large Bile Ducts Intrahepatic Cholangiocarcinoma Classification: A Preliminary Feature-Based Study

Author

Riccardo Muglia, Silvia Conforto, Ezio Lanza, Guido Carpino, Gaetano Giunta, Ana Lleo, Marco Rengo, Andrea Laghi, Maurizio Schmid, Vincenzo Cardinale, Chiara Losquadro, Guido Torzilli, Losquadro, C., Conforto, S., Schmid, M., Giunta, G., Rengo, M., Cardinale, V., Carpino, G., Laghi, A., Lleo, A., Muglia, R., Lanza, E., and Torzilli, G.

Subjects
medicine.medical_specialty, medicine.diagnostic_test, Bile duct, business.industry, Computed Tomography (CT) image, Computed tomography, Classification, Malignancy, medicine.disease, medicine.anatomical_structure, Radiomics, Volumetric CT, Cholangiocarcinoma (CCA), medicine, Feature based, Feature extraction, Radiology, business, Intrahepatic Cholangiocarcinoma
Abstract

Cholangiocarcinoma (CCA) is the second most common liver malignancy and the incidence and mortality rates of this disease are worldwide increasing. This paper deals with the problem of Intrahepatic Cholangiocarcinoma (IH-CCA) classification using Computed Tomography (CT) images. Precisely, a radiomics-based approach is proposed by exploiting abdominal volumetric CT data in order to differentiate large bile duct from small bile duct IH-CCA. The developed method relies on the investigation of intrinsic discriminative properties of CT scans according to feature selection methods. The effectiveness of the proposed method is proved by enrolling in the study a total of 26 patients, including 16 patients with large bile duct and 10 with small bile duct pathological disease, respectively. The conducted tests have shown that our approach is a baseline to provide an efficient classification process with a low computational cost in order to facilitate clinical decision-making procedures.

Published
2021
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9. Mitigation of Speckle Noise in Optical Coherence Tomograms

Author

Silvia Conforto, Mohammadreza Nasiriavanaki, Adrian Gh. Podoleanu, Saba Adabi, Anne Clayton, Ali Hojjat, Adabi, S., Clayton, A., Conforto, S., Hojjat, A., Podoleanu, A. G., and Nasiriavanaki, M.

Subjects
Artificial neural network (ANN), Optical coherence tomography, genetic structures, medicine.diagnostic_test, Computer science, business.industry, Multi-Layer perceptron (MLP), Speckle noise, Perceptron, eye diseases, Speckle noise reduction, Interferometry, Speckle pattern, Software, medicine, Computer vision, sense organs, Artificial intelligence, Tomography, business, Coherence (physics)
Abstract

Optical Coherence Tomography (OCT) is a promising high-resolution imaging technique that works based on low coherent interferometry. However, like other low coherent imaging modalities, OCT suffers from an artifact called, speckle. Speckle reduces the detectability of diagnostically relevant features in the tissue. Retinal optical coherence tomograms are of a great importance in detecting and diagnosing eye diseases. Different hardware or software based techniques are devised in literatures to mitigate speckle noise. The ultimate aim of any software-based despeckling technique is to suppress the noise part of speckle while preserves the information carrying portion of that. In this chapter, we reviewed the most prominent speckle reduction methods for OCT images to date and then present a novel and intelligent speckle reduction algorithm to reduce speckle in OCT images of retina, based on an ensemble framework of Multi-Layer Perceptron (MLP) neural networks.

Published
2018
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