The Experts below are selected from a list of 2232 Experts worldwide ranked by ideXlab platform

Francesco Semeraro - One of the best experts on this subject based on the ideXlab platform.

  • ocular fundus photography with a Smartphone Device in acute hypertension
    Journal of Hypertension, 2017
    Co-Authors: Maria Lorenza Muiesan, M. Riviera, Clara Pintossi, Fabio Bertacchini, Efrem Colonetti, Massimo Salvetti, Anna Paini, M. Poli, Claudia Agabitirosei, Francesco Semeraro
    Abstract:

    Background:The ocular fundus examination is infrequently and poorly performed in the emergency department (ED) clinical settings, placing patients at risk for missed diagnosis of hypertensive emergencies. The aim of this study was to investigate the feasibility of the ocular fundus photography with

  • [OP.8D.06] OCULAR FUNDUS PHOTOGRAPHY WITH A Smartphone Device IN ACUTE HYPERTENSION.
    Journal of Hypertension, 2016
    Co-Authors: Maria Lorenza Muiesan, M. Riviera, Clara Pintossi, Fabio Bertacchini, Efrem Colonetti, Massimo Salvetti, Anna Paini, M. Poli, Francesco Semeraro, E. Agabiti Rosei
    Abstract:

    .OBJECTIVE: \ud The ocular fundus (FO) examination is infrequently and poorly performed in the emergency department (ED) clinical settings, placing patients at risk for missed diagnosis of hypertensive emergencies.\ud AIM: \ud to investigate the feasibility of the FO photography with a Smartphone small optical Device (D-Eye; J Ophtalmol. 2015) in a ED setting and to compare it to a traditional FO examination.\ud \ud DESIGN AND METHOD: \ud The study included 41 consecutive patients (mean age 69 ± 16 years, 50% women) presenting to an hospital ED with an acute increase in blood pressure (SBP >180 and/or DBP >100 mmHg). When admitted to the ED all patients had mydriatic FO examination obtained by an Emergency physician (EP) using both a traditional ophtalmoscope and a commercially available FO Smartphone Device (D-Eye, Si14 S.p.A., Padova). All FO images and videos recorded with the D-Eye system were analysed by 2 independent expert (ophthalmologist) and inexpert (EP) observers. A quantitative score of hemorrages, exudates and/or papillary edema was used (0 absent, 1 early, 2 moderate, 3 severe, 4 very severe). The Cohen K coefficient (Ki) was used to assess the inter-observer concordance index.\ud RESULTS: \ud Six patients had headache, 6 had focal neurologic symptoms, and 4 had acute visual changes. The mean duration of FO examination was 130 ± 39 and 74 ± 31 seconds for traditional ophtalmoscopy and for Smartphone D-Eye, respectively. No relevant abnormalities of their FO were detected by traditional ophthalmoscopy, performed by the EP, while a signifcant number of abnormal FO findings were detected by the use of the D-eye Device in 17 and 19 patients by the EP and ophthalmologist, respectively. The Ki value ranged from 0,66 to 0,77 (good concordance) for the assessment of hemorrages and exudates, and from 0,89 to 0,90 (optimal concordance) for the evaluation of presence and severity of papilledema.\ud CONCLUSIONS: \ud Our results show that a new small Smartphone Device (D-Eye) may be feasible in an ED setting for the fundoscopic examination, detecting a signifcant number of abnormal FO. The reliability of relevant FO abnormalities seems to be superior in respect to traditional fundoscopy

Titus Zaharia - One of the best experts on this subject based on the ideXlab platform.

  • An outdoor cognition system integrated on a regular Smartphone Device
    2015 E-Health and Bioengineering Conference (EHB), 2015
    Co-Authors: Bogdan Mocanu, Ruxandra Tapu, Titus Zaharia
    Abstract:

    In this paper we introduce an assistive Device dedicated to visual impaired / blind people completely integrated on a regular Smartphone. The framework is designed to detect and localize static and dynamic obstacle during user navigation. We start by selecting a reduced and relevant set of FAST interest points based on a regular grid and Harris-Laplacian operator. Then, we construct a global image representation using VLAD (Vector of Locally Aggregated Descriptor) that is further whitened using PCA (Principal Component Analysis). At the end the image patch is fed to a SVM (Support Vector Machine) system that uses a statistical procedure to distinguish between different types of obstacles.

  • An Obstacle Categorization System for Visually Impaired People
    2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), 2015
    Co-Authors: Bogdan Mocanu, Ruxandra Tapu, Titus Zaharia
    Abstract:

    In this paper, we introduce a new framework for obstacle localization and classification. The proposed method is designed to improve cognition of visually impaired people (VI) facilitating the autonomous navigation in outdoor environments. In the context of computer vision applications, the following contributions are proposed and validated: (i) a new method of selecting a reduced and relevant set of interest points, (ii) a novel descriptor denoted Adaptive Histogram of Oriented Gradients (A-HOG) dedicated to arbitrary categories of objects, (iii) an image re-ranking method at Vector of Locally Aggregated Descriptor (VLAD) / Bag of Visual Word (BoVW) descriptor level based on graph spanning structures and neighborhood relations. Finally, we demonstrate the performance of the proposed framework (in terms of classification accuracy and computational time) on a challenging video dataset captured with the help of real VI users. The entire framework is completely integrated on an Android Smartphone Device, while all methods were specifically designed and tuned under the constraint of achieving real-time processing capabilities.

  • a Smartphone based obstacle detection and classification system for assisting visually impaired people
    International Conference on Computer Vision, 2013
    Co-Authors: Ruxandra Tapu, Bogdan Mocanu, Andrei Bursuc, Titus Zaharia
    Abstract:

    In this paper we introduce a real-time obstacle detection and classification system designed to assist visually impaired people to navigate safely, in indoor and outdoor environments, by handling a Smartphone Device. We start by selecting a set of interest points extracted from an image grid and tracked using the multiscale Lucas - Kanade algorithm. Then, we estimate the camera and background motion through a set of homographic transforms. Other types of movements are identified using an agglomerative clustering technique. Obstacles are marked as urgent or normal based on their distance to the subject and the associated motion vector orientation. Following, the detected obstacles are fed/sent to an object classifier. We incorporate HOG descriptor into the Bag of Visual Words (BoVW) retrieval framework and demonstrate how this combination may be used for obstacle classification in video streams. The experimental results demonstrate that our approach is effective in image sequences with significant camera motion and achieves high accuracy rates, while being computational efficient.

Ruxandra Tapu - One of the best experts on this subject based on the ideXlab platform.

  • An outdoor cognition system integrated on a regular Smartphone Device
    2015 E-Health and Bioengineering Conference (EHB), 2015
    Co-Authors: Bogdan Mocanu, Ruxandra Tapu, Titus Zaharia
    Abstract:

    In this paper we introduce an assistive Device dedicated to visual impaired / blind people completely integrated on a regular Smartphone. The framework is designed to detect and localize static and dynamic obstacle during user navigation. We start by selecting a reduced and relevant set of FAST interest points based on a regular grid and Harris-Laplacian operator. Then, we construct a global image representation using VLAD (Vector of Locally Aggregated Descriptor) that is further whitened using PCA (Principal Component Analysis). At the end the image patch is fed to a SVM (Support Vector Machine) system that uses a statistical procedure to distinguish between different types of obstacles.

  • An Obstacle Categorization System for Visually Impaired People
    2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), 2015
    Co-Authors: Bogdan Mocanu, Ruxandra Tapu, Titus Zaharia
    Abstract:

    In this paper, we introduce a new framework for obstacle localization and classification. The proposed method is designed to improve cognition of visually impaired people (VI) facilitating the autonomous navigation in outdoor environments. In the context of computer vision applications, the following contributions are proposed and validated: (i) a new method of selecting a reduced and relevant set of interest points, (ii) a novel descriptor denoted Adaptive Histogram of Oriented Gradients (A-HOG) dedicated to arbitrary categories of objects, (iii) an image re-ranking method at Vector of Locally Aggregated Descriptor (VLAD) / Bag of Visual Word (BoVW) descriptor level based on graph spanning structures and neighborhood relations. Finally, we demonstrate the performance of the proposed framework (in terms of classification accuracy and computational time) on a challenging video dataset captured with the help of real VI users. The entire framework is completely integrated on an Android Smartphone Device, while all methods were specifically designed and tuned under the constraint of achieving real-time processing capabilities.

  • A computer vision system that ensure the autonomous navigation of blind people
    E-Health and Bioengineering Conference (EHB), 2013, 2014
    Co-Authors: Ruxandra Tapu, Mocanu Bogdan, Zaharia Titus
    Abstract:

    In this paper we introduce a real-time obstacle recognition framework designed to alert the visually impaired people/blind of their presence and to assist humans to navigate safely, in indoor and outdoor environments, by handling a Smartphone Device. Static and dynamic objects are detected using interest points selected based on an image grid and tracked using the multiscale Lucas-Kanade algorithm. Next, we activated an object classification methodology. We incorporate HOG (Histogram of Oriented Gradients) descriptor into the BoVW (Bag of Visual Words) retrieval framework and demonstrate how this combination may be used for obstacle classification in video streams. The experimental results performed on various challenging scenes demonstrate that our approach is effective in image sequence with important camera movement, including noise and low resolution data and achieves high accuracy, while being computational efficient.

  • a Smartphone based obstacle detection and classification system for assisting visually impaired people
    International Conference on Computer Vision, 2013
    Co-Authors: Ruxandra Tapu, Bogdan Mocanu, Andrei Bursuc, Titus Zaharia
    Abstract:

    In this paper we introduce a real-time obstacle detection and classification system designed to assist visually impaired people to navigate safely, in indoor and outdoor environments, by handling a Smartphone Device. We start by selecting a set of interest points extracted from an image grid and tracked using the multiscale Lucas - Kanade algorithm. Then, we estimate the camera and background motion through a set of homographic transforms. Other types of movements are identified using an agglomerative clustering technique. Obstacles are marked as urgent or normal based on their distance to the subject and the associated motion vector orientation. Following, the detected obstacles are fed/sent to an object classifier. We incorporate HOG descriptor into the Bag of Visual Words (BoVW) retrieval framework and demonstrate how this combination may be used for obstacle classification in video streams. The experimental results demonstrate that our approach is effective in image sequences with significant camera motion and achieves high accuracy rates, while being computational efficient.

Maria Lorenza Muiesan - One of the best experts on this subject based on the ideXlab platform.

  • ocular fundus photography with a Smartphone Device in acute hypertension
    Journal of Hypertension, 2017
    Co-Authors: Maria Lorenza Muiesan, M. Riviera, Clara Pintossi, Fabio Bertacchini, Efrem Colonetti, Massimo Salvetti, Anna Paini, M. Poli, Claudia Agabitirosei, Francesco Semeraro
    Abstract:

    Background:The ocular fundus examination is infrequently and poorly performed in the emergency department (ED) clinical settings, placing patients at risk for missed diagnosis of hypertensive emergencies. The aim of this study was to investigate the feasibility of the ocular fundus photography with

  • [OP.8D.06] OCULAR FUNDUS PHOTOGRAPHY WITH A Smartphone Device IN ACUTE HYPERTENSION.
    Journal of Hypertension, 2016
    Co-Authors: Maria Lorenza Muiesan, M. Riviera, Clara Pintossi, Fabio Bertacchini, Efrem Colonetti, Massimo Salvetti, Anna Paini, M. Poli, Francesco Semeraro, E. Agabiti Rosei
    Abstract:

    .OBJECTIVE: \ud The ocular fundus (FO) examination is infrequently and poorly performed in the emergency department (ED) clinical settings, placing patients at risk for missed diagnosis of hypertensive emergencies.\ud AIM: \ud to investigate the feasibility of the FO photography with a Smartphone small optical Device (D-Eye; J Ophtalmol. 2015) in a ED setting and to compare it to a traditional FO examination.\ud \ud DESIGN AND METHOD: \ud The study included 41 consecutive patients (mean age 69 ± 16 years, 50% women) presenting to an hospital ED with an acute increase in blood pressure (SBP >180 and/or DBP >100 mmHg). When admitted to the ED all patients had mydriatic FO examination obtained by an Emergency physician (EP) using both a traditional ophtalmoscope and a commercially available FO Smartphone Device (D-Eye, Si14 S.p.A., Padova). All FO images and videos recorded with the D-Eye system were analysed by 2 independent expert (ophthalmologist) and inexpert (EP) observers. A quantitative score of hemorrages, exudates and/or papillary edema was used (0 absent, 1 early, 2 moderate, 3 severe, 4 very severe). The Cohen K coefficient (Ki) was used to assess the inter-observer concordance index.\ud RESULTS: \ud Six patients had headache, 6 had focal neurologic symptoms, and 4 had acute visual changes. The mean duration of FO examination was 130 ± 39 and 74 ± 31 seconds for traditional ophtalmoscopy and for Smartphone D-Eye, respectively. No relevant abnormalities of their FO were detected by traditional ophthalmoscopy, performed by the EP, while a signifcant number of abnormal FO findings were detected by the use of the D-eye Device in 17 and 19 patients by the EP and ophthalmologist, respectively. The Ki value ranged from 0,66 to 0,77 (good concordance) for the assessment of hemorrages and exudates, and from 0,89 to 0,90 (optimal concordance) for the evaluation of presence and severity of papilledema.\ud CONCLUSIONS: \ud Our results show that a new small Smartphone Device (D-Eye) may be feasible in an ED setting for the fundoscopic examination, detecting a signifcant number of abnormal FO. The reliability of relevant FO abnormalities seems to be superior in respect to traditional fundoscopy

Madhavan Jaccob - One of the best experts on this subject based on the ideXlab platform.

  • Pyrene-Based Chemosensor for Picric Acid—Fundamentals to Smartphone Device Design
    Analytical Chemistry, 2019
    Co-Authors: Arunkumar Kathiravan, Annasamy Gowri, Themmila Khamrang, Madhu Deepan Kumar, Namasivayam Dhenadhayalan, Marappan Velusamy, Madhavan Jaccob
    Abstract:

    Developing a fluorescent probe for the selective and sensitive detection of explosives is a topic of continuous research interest. Additionally, underlying the principles behind the detection mechanism is indeed providing substantial information about the design of an efficient fluorescence probe. In this context, a pyrene-tethered 1-(pyridin-2-yl)imidazo[1,5-a]pyridine-based fluorescent probe (TL18) was developed and employed as a fluorescent chemosensor for nitro explosives. The molecular structure of TL18 was well-characterized by NMR and EI-MS spectrometric techniques. UV–visible absorption, steady-state, and time-resolved fluorescence spectroscopic techniques have been employed to explicate the photophysical properties of TL18. The fluorescent nature of the TL18 probe was explored for detection of nitro explosives. Intriguingly, the TL18 probe was selectively responsive to picric acid over other explosives. The quantitative analysis of the fluorescence titration studies of TL18 with picric acid prove...

  • pyrene based chemosensor for picric acid fundamentals to Smartphone Device design
    Analytical Chemistry, 2019
    Co-Authors: Arunkumar Kathiravan, Annasamy Gowri, Themmila Khamrang, Madhu Deepan Kumar, Namasivayam Dhenadhayalan, Marappan Velusamy, Madhavan Jaccob
    Abstract:

    Developing a fluorescent probe for the selective and sensitive detection of explosives is a topic of continuous research interest. Additionally, underlying the principles behind the detection mechanism is indeed providing substantial information about the design of an efficient fluorescence probe. In this context, a pyrene-tethered 1-(pyridin-2-yl)imidazo[1,5-a]pyridine-based fluorescent probe (TL18) was developed and employed as a fluorescent chemosensor for nitro explosives. The molecular structure of TL18 was well-characterized by NMR and EI-MS spectrometric techniques. UV–visible absorption, steady-state, and time-resolved fluorescence spectroscopic techniques have been employed to explicate the photophysical properties of TL18. The fluorescent nature of the TL18 probe was explored for detection of nitro explosives. Intriguingly, the TL18 probe was selectively responsive to picric acid over other explosives. The quantitative analysis of the fluorescence titration studies of TL18 with picric acid prove...