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Article ; Online: Image Quality Comparison between Digital Breast Tomosynthesis Images and 2D Mammographic Images Using the CDMAM Test Object.

Tsalafoutas, Ioannis A / Epistatou, Angeliki C / Delibasis, Konstantinos K

2022 Volume 8, Issue 8

Abstract: To evaluate the image quality (IQ) of synthesized two-dimensional (s2D) and tomographic layer (TL) mammographic images in comparison to the 2D digital mammographic images produced with a new digital breast tomosynthesis (DBT) system. ...

Abstract	To evaluate the image quality (IQ) of synthesized two-dimensional (s2D) and tomographic layer (TL) mammographic images in comparison to the 2D digital mammographic images produced with a new digital breast tomosynthesis (DBT) system.
Language	English
Publishing date	2022-08-21
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2824270-1
ISSN	2313-433X ; 2313-433X
ISSN (online)	2313-433X
ISSN	2313-433X
DOI	10.3390/jimaging8080223
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Article ; Online: Machine learning and features for the prediction of thermal sensation and comfort using data from field surveys in Cyprus.

Pantavou, Katerina / Delibasis, Konstantinos K / Nikolopoulos, Georgios K

International journal of biometeorology

2022 Volume 66, Issue 10, Page(s) 1973–1984

Abstract: Perception can influence individuals' behaviour and attitude affecting responses and compliance to precautionary measures. This study aims to investigate the performance of methods for thermal sensation and comfort prediction. Four machine learning ... ...

Abstract	Perception can influence individuals' behaviour and attitude affecting responses and compliance to precautionary measures. This study aims to investigate the performance of methods for thermal sensation and comfort prediction. Four machine learning algorithms (MLA), artificial neural networks, random forest (RF), support vector machines, and linear discriminant analysis were examined and compared to the physiologically equivalent temperature (PET). Data were collected in field surveys conducted in outdoor sites in Cyprus. The seven- and nine-point assessment scales of thermal sensation and a two-point scale of thermal comfort were considered. The models of MLA included meteorological and physiological features. The results indicate RF as the best MLA applied to the data. All MLA outperformed PET. For thermal sensation, the lowest prediction error (1.32 points) and the highest accuracy (30%) were found in the seven-point scale for the feature vector consisting of air temperature, relative humidity, wind speed, grey globe temperature, clothing insulation, activity, age, sex, and body mass index. The accuracy increased to 63.8% when considering prediction with at most one-point difference from the correct thermal sensation category. The best performed feature vector for thermal sensation also produced one of the best models for thermal comfort yielding an accuracy of 71% and an F-score of 0.81.
MeSH term(s)	Cyprus ; Humans ; Machine Learning ; Temperature ; Thermosensing/physiology ; Wind
Language	English
Publishing date	2022-07-27
Publishing country	United States
Document type	Journal Article
ZDB-ID	280324-0
ISSN	1432-1254 ; 0020-7128
ISSN (online)	1432-1254
ISSN	0020-7128
DOI	10.1007/s00484-022-02333-y
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Article ; Online: Machine learning and features for the prediction of thermal sensation and comfort using data from field surveys in Cyprus

Pantavou, Katerina / Delibasis, Konstantinos K. / Nikolopoulos, Georgios K.

Int J Biometeorol. 2022 Oct., v. 66, no. 10 p.1973-1984

2022

Abstract: Perception can influence individuals’ behaviour and attitude affecting responses and compliance to precautionary measures. This study aims to investigate the performance of methods for thermal sensation and comfort prediction. Four machine learning ... ...

Abstract	Perception can influence individuals’ behaviour and attitude affecting responses and compliance to precautionary measures. This study aims to investigate the performance of methods for thermal sensation and comfort prediction. Four machine learning algorithms (MLA), artificial neural networks, random forest (RF), support vector machines, and linear discriminant analysis were examined and compared to the physiologically equivalent temperature (PET). Data were collected in field surveys conducted in outdoor sites in Cyprus. The seven- and nine-point assessment scales of thermal sensation and a two-point scale of thermal comfort were considered. The models of MLA included meteorological and physiological features. The results indicate RF as the best MLA applied to the data. All MLA outperformed PET. For thermal sensation, the lowest prediction error (1.32 points) and the highest accuracy (30%) were found in the seven-point scale for the feature vector consisting of air temperature, relative humidity, wind speed, grey globe temperature, clothing insulation, activity, age, sex, and body mass index. The accuracy increased to 63.8% when considering prediction with at most one-point difference from the correct thermal sensation category. The best performed feature vector for thermal sensation also produced one of the best models for thermal comfort yielding an accuracy of 71% and an F-score of 0.81.
Keywords	Cyprus ; air temperature ; body mass index ; compliance ; discriminant analysis ; insulating materials ; prediction ; relative humidity ; sensation ; wind speed
Language	English
Dates of publication	2022-10
Size	p. 1973-1984.
Publishing place	Springer Berlin Heidelberg
Document type	Article ; Online
ZDB-ID	127361-9
ISSN	0067-8902 ; 0020-7128
ISSN	0067-8902 ; 0020-7128
DOI	10.1007/s00484-022-02333-y
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Book ; Online: $H$-RANSAC, an algorithmic variant for Homography image transform from featureless point sets

Nousias, George / Delibasis, Konstantinos / Maglogiannis, Ilias

application to video-based football analytics

2023

Abstract: Estimating homography matrix between two images has various applications like image stitching or image mosaicing and spatial information retrieval from multiple camera views, but has been proved to be a complicated problem, especially in cases of ... ...

Abstract	Estimating homography matrix between two images has various applications like image stitching or image mosaicing and spatial information retrieval from multiple camera views, but has been proved to be a complicated problem, especially in cases of radically different camera poses and zoom factors. Many relevant approaches have been proposed, utilizing direct feature based, or deep learning methodologies. In this paper, we propose a generalized RANSAC algorithm, H-RANSAC, to retrieve homography image transformations from sets of points without descriptive local feature vectors and point pairing. We allow the points to be optionally labelled in two classes. We propose a robust criterion that rejects implausible point selection before each iteration of RANSAC, based on the type of the quadrilaterals formed by random point pair selection (convex or concave and (non)-self-intersecting). A similar post-hoc criterion rejects implausible homography transformations is included at the end of each iteration. The expected maximum iterations of $H$-RANSAC are derived for different probabilities of success, according to the number of points per image and per class, and the percentage of outliers. The proposed methodology is tested on a large dataset of images acquired by 12 cameras during real football matches, where radically different views at each timestamp are to be matched. Comparisons with state-of-the-art implementations of RANSAC combined with classic and deep learning image salient point detection indicates the superiority of the proposed $H$-RANSAC, in terms of average reprojection error and number of successfully processed pairs of frames, rendering it the method of choice in cases of image homography alignment with few tens of points, while local features are not available, or not descriptive enough. The implementation of $H$-RANSAC is available in https://github.com/gnousias/H-RANSAC
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	006
Publishing date	2023-10-07
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: A novel device for controlling the flow of information based on Weyl fermions and a method for manipulating the spatial distribution of Weyl particles

Tsigaridas, Georgios N. / Kechriniotis, Aristides I. / Tsonos, Christos A. / Delibasis, Konstantinos K.

2023

Abstract: In this work we propose a novel device for controlling the flow of information using Weyl fermions. In more detail, based on a previous work of our group, we show that it is possible to fully control the flow of Weyl fermions on a sequence of different ... ...

Abstract	In this work we propose a novel device for controlling the flow of information using Weyl fermions. In more detail, based on a previous work of our group, we show that it is possible to fully control the flow of Weyl fermions on a sequence of different channels, by applying an electric field perpendicular to the direction of motion of the particles on each channel. In this way, we can transmit information, logical bits, depending on the existence or not of a Weyl current on each channel. We also show that the response time of this device is exceptionally low, less than 1 ps, for typical values of the parameters, providing the opportunity to control the flow of information at extremely high rates, of the order of 100 Pbps. This device also offers additional advantages, as low power consumption and robustness against electromagnetic perturbations, and is expected to find important applications in several fields, as telecommunications, signal processing, classical and quantum computing, etc. Finally, we demonstrate that Weyl fermions can be efficiently guided through the proposed device using appropriate magnetic fields.
Keywords	Quantum Physics ; Physics - Instrumentation and Detectors
Subject code	621
Publishing date	2023-07-12
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: An Automated Method for Quality Control in MRI Systems: Methods and Considerations.

Epistatou, Angeliki C / Tsalafoutas, Ioannis A / Delibasis, Konstantinos K

Journal of imaging

2020 Volume 6, Issue 10

Abstract: Objective: The purpose of this study was to develop an automated method for performing quality control (QC) tests in magnetic resonance imaging (MRI) systems, investigate the effect of different definitions of QC parameters and its sensitivity with ... ...

Abstract	Objective: The purpose of this study was to develop an automated method for performing quality control (QC) tests in magnetic resonance imaging (MRI) systems, investigate the effect of different definitions of QC parameters and its sensitivity with respect to variations in regions of interest (ROI) positioning, and validate the reliability of the automated method by comparison with results from manual evaluations. Materials and methods: Magnetic Resonance imaging MRI used for acceptance and routine QC tests from five MRI systems were selected. All QC tests were performed using the American College of Radiology (ACR) MRI accreditation phantom. The only selection criterion was that in the same QC test, images from two identical sequential sequences should be available. The study was focused on four QC parameters: percent signal ghosting (PSG), percent image uniformity (PIU), signal-to-noise ratio (SNR), and SNR uniformity (SNRU), whose values are calculated using the mean signal and the standard deviation of ROIs defined within the phantom image or in the background. The variability of manual ROIs placement was emulated by the software using random variables that follow appropriate normal distributions. Results: Twenty-one paired sequences were employed. The automated test results for PIU were in good agreement with manual results. However, the PSG values were found to vary depending on the selection of ROIs with respect to the phantom. The values of SNR and SNRU also vary significantly, depending on the combination of the two out of the four standard rectangular ROIs. Furthermore, the methodology used for SNR and SNRU calculation also had significant effect on the results. Conclusions: The automated method standardizes the position of ROIs with respect to the ACR phantom image and allows for reproducible QC results.
Language	English
Publishing date	2020-10-18
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2824270-1
ISSN	2313-433X ; 2313-433X
ISSN (online)	2313-433X
ISSN	2313-433X
DOI	10.3390/jimaging6100111
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Article ; Online: Measurement and Modeling of Microbial Growth Using Timelapse Video.

Delibasis, Konstantinos / Basanou, Ifigenia / Boulogeorgos, Alexandros-Apostolos A

Sensors (Basel, Switzerland)

2020 Volume 20, Issue 9

Abstract: The development of timelapse videos for the investigation of growing microbial colonies has gained increasing interest due to its low cost and complexity implementation. In the present study, a simple experimental setup is proposed for periodic snapshot ... ...

Abstract	The development of timelapse videos for the investigation of growing microbial colonies has gained increasing interest due to its low cost and complexity implementation. In the present study, a simple experimental setup is proposed for periodic snapshot acquisition of a petri dish cultivating a fungus of the genus Candida SPP, thus creating a timelapse video. A computational algorithm, based on image processing techniques is proposed for estimating the microbial population and for extracting the experimental population curves, showing the time evolution of the population of microbes at any region of the dish. Likewise, a novel mathematical population evolution modeling approach is reported, which is based on the logistic function (LF). Parameter estimation of the aforementioned model is described and visually assessed, in comparison with the conventional and widely-used LF method. The effect of the image analysis parameterization is also highlighted. Our experiments take into account different area sizes, i.e., the number of pixels in the neighborhood, to generate population curves and calculate the model parameters. Our results reveal that, as the size of the area increases, the curve becomes smoother, the signal-to-noise-ratio increases and the estimation of model parameters becomes more accurate.
MeSH term(s)	Algorithms ; Image Processing, Computer-Assisted ; Microbiota/physiology ; Models, Theoretical ; Signal-To-Noise Ratio
Language	English
Publishing date	2020-04-29
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s20092545
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Article ; Online: Impact of personality on the decision process and on satisfaction rates in pseudophakic presbyopic correction.

Ntonti, Panagiota / Bakirtzis, Minas / Delibasis, Konstantinos / Seimenis, Ioannis / Tsinopoulos, Ioannis / Labiris, Georgios

Journal of cataract and refractive surgery

2022 Volume 48, Issue 12, Page(s) 1433–1439

Abstract: Purpose: To explore the impact of personality on the decision process and satisfaction rates in pseudophakic presbyopic correction.: Setting: Department of Ophthalmology, University Hospital of Alexandroupolis, Greece.: Design: Prospective, ... ...

Abstract	Purpose: To explore the impact of personality on the decision process and satisfaction rates in pseudophakic presbyopic correction. Setting: Department of Ophthalmology, University Hospital of Alexandroupolis, Greece. Design: Prospective, comparative study. Methods: A consistent consultation was conducted in patients with cataract that explained the benefits and the drawbacks of bilateral trifocal correction, which was offered at no extra cost. In all participants, personality was evaluated by The Traits Personality Questionnaire 5. Data modeling with decision trees and multiple regression analysis identified the contributions of personality traits to the decision process and postoperative satisfaction. Results: Of 120 participants (60 men and 60 women), 81 (67.5%, 24 men, 57 women) selected premium correction. In men, low neuroticism and high extraversion were the primary personality contributors for selecting premium surgery. In women, all personality traits contributed to the selection process. Women were more demanding in the expected postoperative distant acuity than men (0.1 vs 0.2 logMAR) to present high satisfaction. For both men and women, openness to experience, conscientiousness, and extraversion are primary contributors for optimal satisfaction rates. Conclusions: Men and women demonstrate differences in the selection process for premium pseudophakic surgery and differences in the expected postoperative visual acuity. It seems that the personality of the patient plays a significant role in the perceived outcome after premium surgery.
MeSH term(s)	Male ; Humans ; Female ; Personal Satisfaction ; Prospective Studies ; Personality ; Surveys and Questionnaires ; Cataract
Language	English
Publishing date	2022-07-04
Publishing country	United States
Document type	Journal Article
ZDB-ID	632744-8
ISSN	1873-4502 ; 0886-3350
ISSN (online)	1873-4502
ISSN	0886-3350
DOI	10.1097/j.jcrs.0000000000001021
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Article ; Online: Video-Based Eye Blink Identification and Classification.

Nousias, George / Panagiotopoulou, Eirini-Kanella / Delibasis, Konstantinos / Chaliasou, Aikaterini-Maria / Tzounakou, Anastasia-Maria / Labiris, Georgios

IEEE journal of biomedical and health informatics

2022 Volume 26, Issue 7, Page(s) 3284–3293

Abstract: Blink detection and classification can provide a very useful clinical indicator, because of its relation with many neurological and ophthalmological conditions. In this work, we propose a system that automatically detects and classifies blinks as " ... ...

Abstract	Blink detection and classification can provide a very useful clinical indicator, because of its relation with many neurological and ophthalmological conditions. In this work, we propose a system that automatically detects and classifies blinks as "complete" or "incomplete" in high resolution image sequences zoomed into the participants' face, acquired during clinical examination using near-Infrared illumination. This method utilizes state-of-the-art (DeepLabv3+) deep learning encoder-decoder neural architecture -DLED to segment iris and eyelid in both eyes in the acquired images. The sequence of the segmented frames is post-processed to calculate the distance between the eyelids of each eye (palpebral fissure height) and the corresponding iris diameter. These quantities are temporally filtered and their fraction is subject to adaptive thresholding to identify blinks and determine their type, independently for each eye. The proposed system was tested on 15 participants, each with one video of 4 to 10 minutes. Several metrics of blink detection and classification accuracy were calculated against the ground truth, which was generated by three (3) independent experts, whose conflicts were resolved by a senior expert. Results show that the proposed system achieved F1-score 95.3% and 80.9% for the classification of complete and incomplete blinks respectively, collectively for all 15 participants, outperforming all 3 experts. The proposed system was proven robust in handling unexpected participant movements and actions, as well as glare and reflections from the spectacles, or face obstruction by facemasks.
MeSH term(s)	Blinking ; Eyelids ; Humans ; Infrared Rays
Language	English
Publishing date	2022-07-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	2695320-1
ISSN	2168-2208 ; 2168-2194
ISSN (online)	2168-2208
ISSN	2168-2194
DOI	10.1109/JBHI.2022.3153407
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Article: Lighting Standards Revisited: Introduction of a Mathematical Model for the Assessment of the Impact of Illuminance on Visual Acuity.

Labiris, Georgios / Panagiotopoulou, Eirini-Kanella / Taliantzis, Sergios / Perente, Asli / Delibasis, Konstantinos / Doulos, Lambros T

Clinical ophthalmology (Auckland, N.Z.)

2021 Volume 15, Page(s) 4553–4564

Abstract: Purpose: Primary objective of present study is to introduce a contemporary methodology for the lighting standards update addressing both normophakic and pseudophakic patients.: Methods: For the sake of our study, we theoretically estimated the ... ...

Abstract	Purpose: Primary objective of present study is to introduce a contemporary methodology for the lighting standards update addressing both normophakic and pseudophakic patients. Methods: For the sake of our study, we theoretically estimated the intraocular-to-crystalline lens iIluminance ratio (ICIR) and the intraocular lens (IOL) luminous efficiency function Results: ICIR for Panoptix eyes ranged from 54.00% to 55.99%. Both groups had significantly higher UDVA at 550lx compared to 20lx (p < 0.05). CG had significantly higher UDVA than SG at 20lx (7.20 letters, p = 0.045), while no significant difference was detected at 550lx (0.40 letters, p = 0.883). SG required significantly more illuminance than CG to maintain their UDVA (MRIL Conclusion: This is the first study to introduce the Clinicaltrialsgov identifier: NCT04263636.
Language	English
Publishing date	2021-11-28
Publishing country	New Zealand
Document type	Journal Article
ISSN	1177-5467
ISSN	1177-5467
DOI	10.2147/OPTH.S326139
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