1,217 research outputs found
Labelled Dataset of Retinal Images for Glaucoma detection
No full textFundus photography is a viable option for glaucoma population screening. In order to facilitate the development of computer-aided glaucoma detection systems, we publish this annotation dataset that contains manual annotations of glaucoma features for seven public fundus image data sets. All manual annotations are made by a specialised ophthalmologist. For each of the fundus images in the seven fundus datasets, the upper, the bottom, the left and the right boundary coordinates of the optic disc and the cup are stored in a .mat file with the corresponding fundus image name.
The seven public fundus image data sets are:
CHASEDB (https://blogs.kingston.ac.uk/retinal/chasedb1/),
Diaretdb1_v_1_1 (https://www.it.lut.fi/project/imageret/diaretdb1/),
DRINSHTI (http://cvit.iiit.ac.in/projects/mip/drishti-gs/mip-dataset2/Home.php),
DRIONS-DB (http://www.ia.uned.es/~ejcarmona/DRIONS-DB.html),
DRIVE (https://www.isi.uu.nl/Research/Databases/DRIVE/),
HRF (https://www5.cs.fau.de/research/data/fundus-images/), and
Messidor (http://www.adcis.net/en/Download-Third-Party/Messidor.html).
Researchers are encouraged to use this set to train or validate their systems for automatic glaucoma detection. When you use this set, please cite our published paper:
J. Guo, G. Azzopardi, C. Shi, N. M. Jansonius and N. Petkov, "Automatic Determination of Vertical Cup-to-Disc Ratio in Retinal Fundus Images for Glaucoma Screening," in IEEE Access, vol. 7, pp. 8527-8541, 2019, doi: 10.1109/ACCESS.2018.2890544.
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Child and Adolescent Mortality Across Malaysia's Epidemiological Transition: A Systematic Analysis of Global Burden of Disease Data
No full textAbstract not AvailableSuraya Abdul-Razak, Peter S. Azzopardi, George C. Patton, Ali H. Mokdad and Susan M. Sawye
Health in All Policies
No full textchapter 16: Health in All Policies A Lazzari, C de Waure, N Azzopardi-Muscat - A Systematic Review of Key Issues in …, 2015 ... of Health Services Management, Faculty of Health Sciences, University of Malta, Msida, Malt
Ventral-stream-like shape representation: from pixel intensity values to trainable object-selective COSFIRE models
No full textThe remarkable abilities of the primate visual cortex have inspired the construction of computational models of some visual neurons. We propose a trainable hierarchical object recognition model, which we call S-COSFIRE (S stands for Shape and COSFIRE stands for Combination Of Shifted FIlter REsponses) and use it to localize and recognize objects of interests embedded in complex scenes. It is inspired by the visual processing in the ventral stream (V1/V2 -> V4 -> TEO). Recognition and localization of objects embedded in complex scenes is important for many computer vision applications. Most existing methods require prior segmentation of the objects from the background which on its turn requires recognition. A S-COSFIRE filter is automatically configured to be selective for an arrangement of contour-based features that belong to a prototype shape specified by an example. The configuration comprises selecting relevant vertex detectors and determining certain blur and shift parameters. The response is computed as the weighted geometric mean of the blurred and shifted responses of the selected vertex detectors. S-COSFIRE filters share similar properties with some neurons in inferotemporal cortex, which provided inspiration for this work. We demonstrate the effectiveness of S-COSFIRE filters in two applications: letter and keyword spotting in handwritten manuscripts and object spotting in complex scenes for the computer vision system of a domestic robot. S-COSFIRE filters are effective to recognize and localize (deformable) objects in images of complex scenes without requiring prior segmentation. They are versatile trainable shape detectors, conceptually simple and easy to implement. The presented hierarchical shape representation contributes to a better understanding of the brain and to more robust computer vision algorithms
[Ġabra ta’ kitbiet : Il-Malti, Ħarġa 3]. Sajf ; Non omnis moriar... ; Inżul ix-xemx ; Xagħar safrani ; Tifkiriet.
No full textĠabra ta’ poeżiji u proża li tinkludi: Sajf ta’ Dun Pietru Pawl – Non omnis moriar... ta’ Dun Karm – Inżul ix-xemx ta’ Ġidi – Xagħar safrani ta’ Ġino Muscat Azzopardi – Tifkiriet ta’ C. M. B.N/
Using the quantum probability ranking principle to rank interdependent documents
No full textA known limitation of the Probability Ranking Principle (PRP) is that it does not cater for dependence between documents. Recently, the Quantum Probability Ranking Principle (QPRP) has been proposed, which implicitly captures dependencies between documents through “quantum interference”. This paper explores whether this new ranking principle leads to improved performance for subtopic retrieval, where novelty and diversity is required. In a thorough empirical investigation, models based on the PRP, as well as other recently proposed ranking strategies for subtopic retrieval (i.e. Maximal Marginal Relevance (MMR) and Portfolio Theory(PT)), are compared against the QPRP. On the given task, it is shown that the QPRP outperforms these other ranking strategies. And unlike MMR and PT, one of the main advantages of the QPRP is that no parameter estimation/tuning is required; making the QPRP both simple and effective. This research demonstrates that the application of quantum theory to problems within information retrieval can lead to significant improvements
Geologic map of the Dufur area, Wasco County, Oregon
No full textReport -- Plate 1 -- Plate 2 -- Plate 3.Jason D. McClaughry, Heather H. Herinckx, Clark A. Niewendorp, Carlie J.M. Azzopardi, and Joshua A. Hackett.Title from PDF cover (viewed on May 19, 2021).This archived document is maintained by the State Library of Oregon as part of the Oregon Documents Depository Program. It is for informational purposes and may not be suitable for legal purposes.Includes bibliographical references.Mode of access: Internet from the Oregon Government Publications Collection.Text in English
Hepatitis C : an emerging concern
No full textHepatitis C has surfaced worldwide as a formidable concern to public health. Recent developments have sharpened methods of serological detectability, epidemiological study and patient treatment. In the light of the global situation, this article briefly presents known local epidemiology about hepatitis C derived from routine data and personal communication from some key workers. The occurrence of a serious, potentially progressive, transmissible condition in a young population will incur high-costs to patients, contacts and care services. The article concludes by highlighting the areas offering greatest scope to check this condition through prevention and patient management.peer-reviewe
La Croce dei Cavalieri di Malta: Emblema-gioiello nell'area Mediterranea
No full textIl saggio presenta una selezione delle principali croci di Malta emblema - gioiello in musei e collezioni private d'Europa con particolare riferimento alle opere di produzione sicilian
Trainable COSFIRE Filters for Keypoint Detection and Pattern Recognition
No full textBackground: Keypoint detection is important for many computer vision applications. Existing methods suffer from insufficient selectivity regarding the shape properties of features and are vulnerable to contrast variations and to the presence of noise or texture. Methods: We propose a trainable filter which we call Combination Of Shifted FIlter REsponses (COSFIRE) and use for keypoint detection and pattern recognition. It is automatically configured to be selective for a local contour pattern specified by an example. The configuration comprises selecting given channels of a bank of Gabor filters and determining certain blur and shift parameters. A COSFIRE filter response is computed as the weighted geometric mean of the blurred and shifted responses of the selected Gabor filters. It shares similar properties with some shape-selective neurons in visual cortex, which provided inspiration for this work. Results: We demonstrate the effectiveness of the proposed filters in three applications: the detection of retinal vascular bifurcations (DRIVE dataset: 98.50 percent recall, 96.09 percent precision), the recognition of handwritten digits (MNIST dataset: 99.48 percent correct classification), and the detection and recognition of traffic signs in complex scenes (100 percent recall and precision). Conclusions: The proposed COSFIRE filters are conceptually simple and easy to implement. They are versatile keypoint detectors and are highly effective in practical computer vision applications.
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