368 research outputs found
Medical Imaging: Principles, Detectors, and Electronics [Book Reviews]
No full textMoratal, D. (2011). Medical Imaging: Principles, Detectors, and Electronics [Book Reviews]. IEEE Engineering in Medicine and Biology Magazine. 2(3):76-77. doi:10.1109/MPUL.2011.941527S76772
Practical Biomedical Signal Analysis using MATLAB
No full textMoratal Pérez, D. (2012). Practical Biomedical Signal Analysis using MATLAB. IEEE Pulse. 3(5):60-60. doi:10.1109/MPUL.2012.2205847S60603
Principles of Computational Modelling in Neuroscience
No full textMoratal Pérez, D. (2012). Principles of Computational Modelling in Neuroscience. IEEE Pulse. 3(4):82-82. doi:10.1109/MPUL.2012.2196841S82823
Investigations of strength and energy absorption of clinched joints
No full textWith an increasing application of clinching in different industrial fields, the demand for a better understanding of the knowledge of static and dynamic characteristics of the clinched joints is required. In this paper, the clinching process and tensile-shear failure of the clinched joints have been numerically simulated using finite element (FE) method. For validating the numerical simulations, experimental tests on specimens made of aluminium alloy have been carried out. The results obtained from tests agreed fairly well with the computational simulation. Tensile-shear tests were carried out to measure the ultimate tensile-shear strengths of the clinching joints and clinching-bonded hybrid joints. Deformation and failure of joints under tensile-shear loading were studied. The normal hypothesis tests were performed to examine the rationality of the test data. This work was also aimed at evaluating experimentally and comparing the strength and energy absorption of the clinched joints and clinching-bonded hybrid joints
Radiomics in Alzheimer's Disease: seeking new imaging biomarkers to identify the early stages of the disease
No full text[EN] The valuable intrinsic information contained in many medical images has been
under-exploited for too long. Now, new and rapidly developing technological
advances for the acquisition of high-quality images and the processing of the
underlying information in a rapid and intelligent way are allowing use of these ¿hidden¿ data, with the potential to revolutionize the field of radiology. The advances
already achieved by this approach in oncology are sufficiently encouraging to justify its application to other difficult clinical challenges such as the diagnosis and
staging of Alzheimer¿s disease (AD).
This article summarizes the current status of radiomics analysis in AD and
describes the potential of newly developed software for the identification of image
texture biomarkersDavid Moratal acknowledges financial support from the Conselleria d¿Educació, Investigació, Cultura i Esport, Generalitat Valenciana (grants AEST/2018/021 and AEST/2019/037Ortiz-Ramón, R.; Moratal, D. (2019). Radiomics in Alzheimer's Disease: seeking new imaging biomarkers to identify the early stages of the disease. Diagnostic Imaging Europe. 35(4):10-13. https://riunet.upv.es/handle/10251/165612S101335
A generalized entropy-based two-phase threshold algorithm for noisy medical image edge detection
No full text[EN] Edge detection in medical imaging is a significant task for object recognition of human organs and is considered a pre-processing step in medical image segmentation and reconstruction. This article proposes an efficient approach based on generalized Hill entropy to find a good solution for detecting edges under noisy conditions in medical images. The proposed algorithm uses a two-phase thresholding: firstly, a global threshold calculated by means of generalized Hill entropy is used to separate the image into object and background. Afterwards, a local threshold value is determined for each part of the image. The final edge map image is a combination of these two separate images based on the three calculated thresholds. The performance of the proposed algorithm is compared to Canny and Tsallis entropy using sets of medical images corrupted by various types of noise. We used Pratt's Figure Of Merit (PFOM) as a quantitative measure for an objective comparison. Experimental results indicated that the proposed algorithm displayed superior noise resilience and better edge detection than Canny and Tsallis entropy methods for the four different types of noise analyzed, and thus it can be considered as a very interesting edge detection algorithm on noisy medical images. (c) 2017 Sharif University of Technology. All rights reserved.This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and by FEDER funds under Grant BFU2015-64380-C2-2-R.Elaraby, A.; Moratal, D. (2017). A generalized entropy-based two-phase threshold algorithm for noisy medical image edge detection. Scientia Iranica. 24(6):3247-3256. https://doi.org/10.24200/sci.2017.4359S3247325624
Computer-Aided Detection of Brain Metastases using a Three-Dimensional Template-Based Matching Algorithm
No full textThe purpose of this work was to develop an algorithm for detecting brain metastases in magnetic resonance imaging (MRI), emphasizing the reduction of false positives. Firstly, three-dimensional templates were cross-correlated with the brain volume. Afterwards, each lesion candidate was segmented in the three orthogonal views as a previous step to remove elongated structures such as blood vessels. In a database containing 19 patients and 62 brain metastases, detection algorithm showed a sensitivity of 93.55%. After applying the method for false positive reduction, encouraging results were obtained: false positive rate per slice decreased from 0.64 to 0.15 and only one metastasis was removed, leading to a sensitivity of 91.94%.Pérez Ramírez, MÚ.; Arana Fernandez De Moya, E.; Moratal Pérez, D. (2014). Computer-Aided Detection of Brain Metastases using a Three-Dimensional Template-Based Matching Algorithm. IEEE Engineering in Medicine and Biology Society. Conference Proceedings. 2014:2384-2387. doi:10.1109/EMBC.2014.6944101S23842387201
Automatic detection of local Arterial Input Functions through Independent Component Analysis on dynamic contrast enhanced magnetic resonance imaging
No full textArterial Input Function (AIF) is obtained from perfusion studies as a basic parameter for the calculus of hemodynamic variables used as surrogate markers of the vascular status of tissues. However, at present, its identification is made manually leading to high subjectivity, low repeatability and considerable time consumption. We propose an alternative method to automatically identify local AIF in perfusion images using Independent Component Analysis.Narváez, M.; Ruiz España, S.; Arana Fernandez De Moya, E.; Moratal Pérez, D. (2015). Automatic detection of local Arterial Input Functions through Independent Component Analysis on dynamic contrast enhanced magnetic resonance imaging. IEEE Engineering in Medicine and Biology Society. Conference Proceedings. 4294-4297. doi:10.1109/EMBC.2015.7319344S4294429
Rompepernos o expansión térmica del agua
No full textEn este video se pretende ofrecer una explicación sobre la expansión térmica del agua y porqué ésta presenta un comportamiento anormal con la temperatura. Se hará uso de un rompepernos para romper una barra de hierro congelando una pequeña cantidad de agua.https://media.upv.es/#/portal/video/c2a79af0-be4f-11eb-9ced-87fecb69edb2Cañada Soriano, M.; Moratal Pérez, D.; Rodríguez Hernández, JC.; Vallés Lluch, A.; Vilariño Feltrer, G. (2021). Rompepernos o expansión térmica del agua. Universitat Politècnica de València. https://riunet.upv.es/handle/10251/167483DE
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