966 resultados para cancer detection


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The most significant radiation field nonuniformity is the well-known Heel effect. This nonuniform beam effect has a negative influence on the results of computer-aided diagnosis of mammograms, which is frequently used for early cancer detection. This paper presents a method to correct all pixels in the mammography image according to the excess or lack on radiation to which these have been submitted as a result of the this effect. The current simulation method calculates the intensities at all points of the image plane. In the simulated image, the percentage of radiation received by all the points takes the center of the field as reference. In the digitized mammography, the percentages of the optical density of all the pixels of the analyzed image are also calculated. The Heel effect causes a Gaussian distribution around the anode-cathode axis and a logarithmic distribution parallel to this axis. Those characteristic distributions are used to determine the center of the radiation field as well as the cathode-anode axis, allowing for the automatic determination of the correlation between these two sets of data. The measurements obtained with our proposed method differs on average by 2.49 mm in the direction perpendicular to the anode-cathode axis and 2.02 mm parallel to the anode-cathode axis of commercial equipment. The method eliminates around 94% of the Heel effect in the radiological image and the objects will reflect their x-ray absorption. To evaluate this method, experimental data was taken from known objects, but could also be done with clinical and digital images.

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This report is the fourth annual report based on key program activity, performance and outcome indicators to monitor the achievements of the BreastScreen Australia Program. The report presents the most recent information on participation in breast screening, cancer detection, program sensitivity and recall to assessment and rescreening rates.

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This report is the fifth annual report based on key program activity, performance and outcome indicators to monitor the achievements of the BreastScreen Australia Program. The report presents the most recent information on participation in breast screening, cancer detection, program sensitivity and recall to assessment and rescreening rates. In addition, the report presents national breast cancer incidence and mortality data to provide a context for these indicators of screening activity. Where possible, the data are presented by state and territory as well as nationally.

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Penile carcinoma (PeCa) represents an important public health problem in poor and developing countries. Despite its unpredictable behavior and aggressive treatment, there have only been a few reports regarding its molecular data, especially epigenetic mechanisms. The functional diversity in different cell types is acquired by chromatin modifications, which are established by epigenetic regulatory mechanisms involving DNA methylation, histone acetylation, and miRNAs. Recent evidence indicates that the dysregulation in these processes can result in the development of several diseases, including cancer. Epigenetic alterations, such as the methylation of CpGs islands, may reveal candidates for the development of specific markers for cancer detection, diagnosis and prognosis. There are a few reports on the epigenetic alterations in PeCa, and most of these studies have only focused on alterations in specific genes in a limited number of cases. This review aims to provide an overview of the current knowledge of the epigenetic alterations in PeCa and the promising results in this field. The identification of epigenetically altered genes in PeCa is an important step in understanding the mechanisms involved in this unexplored disease. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

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Pós-graduação em Bases Gerais da Cirurgia - FMB

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This paper presents a Computer Aided Diagnosis (CAD) system that automatically classifies microcalcifications detected on digital mammograms into one of the five types proposed by Michele Le Gal, a classification scheme that allows radiologists to determine whether a breast tumor is malignant or not without the need for surgeries. The developed system uses a combination of wavelets and Artificial Neural Networks (ANN) and is executed on an Altera DE2-115 Development Kit, a kit containing a Field-Programmable Gate Array (FPGA) that allows the system to be smaller, cheaper and more energy efficient. Results have shown that the system was able to correctly classify 96.67% of test samples, which can be used as a second opinion by radiologists in breast cancer early diagnosis. (C) 2013 The Authors. Published by Elsevier B.V.

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In der vorliegenden Studie wurde überprüft, ob Broschüren, die negative Konsequenzen unzureichender Hautselbstuntersuchung (HSU) betonen (Verlustrahmung), besser geeignet sind, die Früherkennung von Hautkrebs zu fördern als Broschüren, die positive Konsequenzen bei richtig durchgeführter HSU schildern (Gewinnrahmung). Geschlecht und die Bewältigungsdispositionen Vigilanz und kognitive Vermeidung wurden als mögliche Moderatorvariablen untersucht. Nach Erfassung von Baseline- und Hintergrundvariablen lasen 180 Teilnehmer jeweils eine der Broschüren, die ihnen per Zufall zugeteilt wurde. Diese variierten in Rahmung (Gewinn/Verlust) und Bedrohungsgrad (gering/hoch), so dass vier unterschiedliche Versionen vorlagen. Rahmung und Bedrohungsgrad wirkten sich in Abhängigkeit von Vigilanz, d.h. der Disposition, bedrohungsbezogene Informationen systematisch zu verarbeiten, auf die Intention aus. Deutlicher war die Wirkung der Rahmung auf die berichtete Häufigkeit von HSU, die zwei Monate nach dem Lesen erneut erfragt worden war. In der Verlustbedingung stieg die berichtete Häufigkeit von HSU bei Personen mit hoher Vigilanz, bei Personen mit niedriger Vigilanz dagegen sank sie. In der Gewinnbedingung profitierten Personen mit niedriger Vigilanz, während Personen mit hoher Vigilanz weniger HSU berichteten als zuvor. Diese Effekte korrespondierten zwar mit Änderungen der eigenen Risikowahrnehmung, der Erinnerungsleistung und der Beschäftigung mit dem Studienthema, jedoch ließ sich für keine dieser Variablen eine vermittelnde Wirkung nachweisen. Einstellung und Anforderung von Informationsmaterialien blieben unbeeinflusst.

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Ultrasound imaging is widely used in medical diagnostics as it is the fastest, least invasive, and least expensive imaging modality. However, ultrasound images are intrinsically difficult to be interpreted. In this scenario, Computer Aided Detection (CAD) systems can be used to support physicians during diagnosis providing them a second opinion. This thesis discusses efficient ultrasound processing techniques for computer aided medical diagnostics, focusing on two major topics: (i) Ultrasound Tissue Characterization (UTC), aimed at characterizing and differentiating between healthy and diseased tissue; (ii) Ultrasound Image Segmentation (UIS), aimed at detecting the boundaries of anatomical structures to automatically measure organ dimensions and compute clinically relevant functional indices. Research on UTC produced a CAD tool for Prostate Cancer detection to improve the biopsy protocol. In particular, this thesis contributes with: (i) the development of a robust classification system; (ii) the exploitation of parallel computing on GPU for real-time performance; (iii) the introduction of both an innovative Semi-Supervised Learning algorithm and a novel supervised/semi-supervised learning scheme for CAD system training that improve system performance reducing data collection effort and avoiding collected data wasting. The tool provides physicians a risk map highlighting suspect tissue areas, allowing them to perform a lesion-directed biopsy. Clinical validation demonstrated the system validity as a diagnostic support tool and its effectiveness at reducing the number of biopsy cores requested for an accurate diagnosis. For UIS the research developed a heart disease diagnostic tool based on Real-Time 3D Echocardiography. Thesis contributions to this application are: (i) the development of an automated GPU based level-set segmentation framework for 3D images; (ii) the application of this framework to the myocardium segmentation. Experimental results showed the high efficiency and flexibility of the proposed framework. Its effectiveness as a tool for quantitative analysis of 3D cardiac morphology and function was demonstrated through clinical validation.

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Hintergrund: Die Systembiopsie gilt als Goldstandard zum Nachweis eines Prostatakarzinoms, obwohl ein relevanter Anteil an Prostatakarzinomen nicht diagnostiziert wird. Wir wollten mit unserer Arbeit die Frage beantworten, ob mittels elastographisch gezielter Biopsien die Prostatakarzinom-Detektion im Vergleich zur Goldstandard-Systembiopsie verbessert werden kann. Material und Methode: 152 Patienten wurden in einer prospektiven Studie einer 12-fachen Prostata-Systembiopsie unterzogen. In Linksseitenlagerung wurde dabei aus jedem der vordefinierten 6 Prostatasegmente je 1 laterale und 1 mediale Stanze entnommen. Elastographisch suspekte Areale wurden zusätzlich gezielt biopsiert. Als statistisch signifikant wurde p<0,05 angenommen. Ergebnisse: Bei 62 der 152 Patienten (40,8%) wurde ein Prostatakarzinom diagnostiziert. Die Detektionsrate der Systembiopsie betrug 39,5% (60/152), die Detektionsrate der Elastographie 29,6% (45/152). Somit war die Systembiopsie der elastographisch gezielten Biopsie signifikant überlegen (p=0,039).Jedoch war die Wahrscheinlichkeit mit einer Prostatastanze ein Karzinomherd zu entdecken, für die elastographischen Biopsien 3,7-fach höher als für die Systembiopsien. Die Sensitivität der Elastographie betrug 72,6% und die Spezifität 66,6%. Der positive Vorhersagewert für die Elastographie war 60%, der negative Vorhersagewert 78%. Die Kombination von Systembiopsie und elastographisch gezielten Biopsien bot die höchste Detektionsrate. In der rechten Prostatahälfte (48%) verzeichneten wir doppelt so viele elastographisch falsch-positive Befunde wie in der linken Prostatahälfte (25%). Desweiteren fanden sich am häufigsten falsch-positive Befunde im Prostata-Apex (46%) und am seltensten in der Prostata-Basis (29%). Schlussfolgerung: In unserer Studie war die elastographisch gezielte Biopsie der Systembiopsie signifikant unterlegen (p=0,039). Die Kombination von Systembiopsie mit elastographisch gezielten Biopsien bot die höchste Detektionsrate und kann daher empfohlen werden. Die Auffälligkeiten in der Segment-bezogenen Auswertung und ein möglicher Einfluss der Patienten-Lagerung müssen durch weitere Studien überprüft werden.rn

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The problem of localizing a scatterer, which represents a tumor, in a homogeneous circular domain, which represents a breast, is addressed. A breast imaging method based on microwaves is considered. The microwave imaging involves to several techniques for detecting, localizing and characterizing tumors in breast tissues. In all such methods an electromagnetic inverse scattering problem exists. For the scattering detection method, an algorithm based on a linear procedure solution, inspired by MUltiple SIgnal Classification algorithm (MUSIC) and Time Reversal method (TR), is implemented. The algorithm returns a reconstructed image of the investigation domain in which it is detected the scatterer position. This image is called pseudospectrum. A preliminary performance analysis of the algorithm vying the working frequency is performed: the resolution and the signal-to-noise ratio of the pseudospectra are improved if a multi-frequency approach is considered. The Geometrical Mean-MUSIC algorithm (GM- MUSIC) is proposed as multi-frequency method. The performance of the GMMUSIC is tested in different real life computer simulations. The performed analysis shows that the algorithm detects the scatterer until the electrical parameters of the breast are known. This is an evident limit, since, in a real life situation, the anatomy of the breast is unknown. An improvement in GM-MUSIC is proposed: the Eye-GMMUSIC algorithm. Eye-GMMUSIC algorithm needs no a priori information on the electrical parameters of the breast. It is an optimizing algorithm based on the pattern search algorithm: it searches the breast parameters which minimize the Signal-to-Clutter Mean Ratio (SCMR) in the signal. Finally, the GM-MUSIC and the Eye-GMMUSIC algorithms are tested on a microwave breast cancer detection system consisting of an dipole antenna, a Vector Network Analyzer and a novel breast phantom built at University of Bologna. The reconstruction of the experimental data confirm the GM-MUSIC ability to localize a scatterer in a homogeneous medium.

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OBJECTIVES: To assess the use and appropriateness of medical advice for smoking cessation provided by registrars in a General Medicine Outpatient Department to an unselected patient population in Switzerland. METHODS: A prospective observational study in which 314 consecutive outpatients were contacted by phone within 24h after their consultation. Questions and information concerning smoking asked and/or provided by the registrar to patients were collected. RESULTS: Eleven registrars (mean age 34 years (range 29-40), 54% females, mean of 5 years (range 3.5-6 years) postgraduate medical training) worked in the Basel University Hospital Medical Outpatient Department during the study period from 01.01.2006 to 31.03.2006. In total 314 participants (mean 48 years, age range 16-71 years, 50% females) completed the study. Registrars queried 81% of the patients about smoking, but inquired about smoking duration only in 44% of the patients. Twenty-eight percent of the patients received information about the risks related to smoking, whereas cessation was discussed only with 10% and offered to 9% of the patients. CONCLUSION: Though most junior physicians in the survey asked about smoking, they failed to appropriately address tobacco-related health issues and offer cessation advice in the majority of cases. Extended regular training for physicians on smoking-related issues will be necessary in order to improve counselling of smokers and meet the global tobacco challenge.

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OBJECTIVE: We sought to evaluate the performance of the human papillomavirus high-risk DNA test in patients 30 years and older. MATERIALS AND METHODS: Screening (n=835) and diagnosis (n=518) groups were defined based on prior Papanicolaou smear results as part of a clinical trial for cervical cancer detection. We compared the Hybrid Capture II (HCII) test result with the worst histologic report. We used cervical intraepithelial neoplasia (CIN) 2/3 or worse as the reference of disease. We calculated sensitivities, specificities, positive and negative likelihood ratios (LR+ and LR-), receiver operating characteristic (ROC) curves, and areas under the ROC curves for the HCII test. We also considered alternative strategies, including Papanicolaou smear, a combination of Papanicolaou smear and the HCII test, a sequence of Papanicolaou smear followed by the HCII test, and a sequence of the HCII test followed by Papanicolaou smear. RESULTS: For the screening group, the sensitivity was 0.69 and the specificity was 0.93; the area under the ROC curve was 0.81. The LR+ and LR- were 10.24 and 0.34, respectively. For the diagnosis group, the sensitivity was 0.88 and the specificity was 0.78; the area under the ROC curve was 0.83. The LR+ and LR- were 4.06 and 0.14, respectively. Sequential testing showed little or no improvement over the combination testing. CONCLUSIONS: The HCII test in the screening group had a greater LR+ for the detection of CIN 2/3 or worse. HCII testing may be an additional screening tool for cervical cancer in women 30 years and older.

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Objective. To evaluate the diagnostic benefit of real-time elastography (RTE) in clinical routine. Strain indices (SI) for benign and malignant tumors were assessed. Methods. 100 patients with 110 focal breast lesions were retrieved. Patients had mammography (MG), ultrasound (US), and, if necessary, MRI. RTE was conducted after ultrasound. Lesions were assessed with BI-RADS for mammography and ultrasound. Diagnosis was established with histology or follow-up. Results. SI for BI-RADS 2 was 1.71 ± 0.86. Higher SI (2.21 ± 1.96) was observed for BI-RADS 3 lesions. SI of BI-RADS 4 and 5 lesions were significantly higher (16.92 ± 20.89) and (19.54 ± 10.41). 31 malignant tumors exhibited an average SI of 16.13 ± 14.67; SI of benign lesions was 5.29 ± 11.87 (P value <0.0001). ROC analysis threshold was >3.8 for malignant disease. Sensitivity of sonography was 90.3% (specificity 78.5%). RTE showed a sensitivity of 87.1% (specificity 79.7%). Accuracy of all modalities combined was 96.8%. In BI-RADS 3 lesions RTE was able to detect all malignant lesions (sensitivity 100%, specificity 92.9%, and accuracy 93.9%). Conclusions. RTE increased sensitivity and specificity for breast cancer detection when used in combination with ultrasound.

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El análisis de imágenes hiperespectrales permite obtener información con una gran resolución espectral: cientos de bandas repartidas desde el espectro infrarrojo hasta el ultravioleta. El uso de dichas imágenes está teniendo un gran impacto en el campo de la medicina y, en concreto, destaca su utilización en la detección de distintos tipos de cáncer. Dentro de este campo, uno de los principales problemas que existen actualmente es el análisis de dichas imágenes en tiempo real ya que, debido al gran volumen de datos que componen estas imágenes, la capacidad de cómputo requerida es muy elevada. Una de las principales líneas de investigación acerca de la reducción de dicho tiempo de procesado se basa en la idea de repartir su análisis en diversos núcleos trabajando en paralelo. En relación a esta línea de investigación, en el presente trabajo se desarrolla una librería para el lenguaje RVC – CAL – lenguaje que está especialmente pensado para aplicaciones multimedia y que permite realizar la paralelización de una manera intuitiva – donde se recogen las funciones necesarias para implementar dos de las cuatro fases propias del procesado espectral: reducción dimensional y extracción de endmembers. Cabe mencionar que este trabajo se complementa con el realizado por Raquel Lazcano en su Proyecto Fin de Grado, donde se desarrollan las funciones necesarias para completar las otras dos fases necesarias en la cadena de desmezclado. En concreto, este trabajo se encuentra dividido en varias partes. La primera de ellas expone razonadamente los motivos que han llevado a comenzar este Proyecto Fin de Grado y los objetivos que se pretenden conseguir con él. Tras esto, se hace un amplio estudio del estado del arte actual y, en él, se explican tanto las imágenes hiperespectrales como los medios y las plataformas que servirán para realizar la división en núcleos y detectar las distintas problemáticas con las que nos podamos encontrar al realizar dicha división. Una vez expuesta la base teórica, nos centraremos en la explicación del método seguido para componer la cadena de desmezclado y generar la librería; un punto importante en este apartado es la utilización de librerías especializadas en operaciones matriciales complejas, implementadas en C++. Tras explicar el método utilizado, se exponen los resultados obtenidos primero por etapas y, posteriormente, con la cadena de procesado completa, implementada en uno o varios núcleos. Por último, se aportan una serie de conclusiones obtenidas tras analizar los distintos algoritmos en cuanto a bondad de resultados, tiempos de procesado y consumo de recursos y se proponen una serie de posibles líneas de actuación futuras relacionadas con dichos resultados. ABSTRACT. Hyperspectral imaging allows us to collect high resolution spectral information: hundred of bands covering from infrared to ultraviolet spectrum. These images have had strong repercussions in the medical field; in particular, we must highlight its use in cancer detection. In this field, the main problem we have to deal with is the real time analysis, because these images have a great data volume and they require a high computational power. One of the main research lines that deals with this problem is related with the analysis of these images using several cores working at the same time. According to this investigation line, this document describes the development of a RVC – CAL library – this language has been widely used for working with multimedia applications and allows an optimized system parallelization –, which joins all the functions needed to implement two of the four stages of the hyperspectral imaging processing chain: dimensionality reduction and endmember extraction. This research is complemented with the research conducted by Raquel Lazcano in her Diploma Project, where she studies the other two stages of the processing chain. The document is divided in several chapters. The first of them introduces the motivation of the Diploma Project and the main objectives to achieve. After that, we study the state of the art of some technologies related with this work, like hyperspectral images and the software and hardware that we will use to parallelize the system and to analyze its performance. Once we have exposed the theoretical bases, we will explain the followed methodology to compose the processing chain and to generate the library; one of the most important issues in this chapter is the use of some C++ libraries specialized in complex matrix operations. At this point, we will expose the results obtained in the individual stage analysis and then, the results of the full processing chain implemented in one or several cores. Finally, we will extract some conclusions related with algorithm behavior, time processing and system performance. In the same way, we propose some future research lines according to the results obtained in this document

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Las imágenes hiperespectrales permiten extraer información con una gran resolución espectral, que se suele extender desde el espectro ultravioleta hasta el infrarrojo. Aunque esta tecnología fue aplicada inicialmente a la observación de la superficie terrestre, esta característica ha hecho que, en los últimos años, la aplicación de estas imágenes se haya expandido a otros campos, como la medicina y, en concreto, la detección del cáncer. Sin embargo, este nuevo ámbito de aplicación ha generado nuevas necesidades, como la del procesado de las imágenes en tiempo real. Debido, precisamente, a la gran resolución espectral, estas imágenes requieren una elevada capacidad computacional para ser procesadas, lo que imposibilita la consecución de este objetivo con las técnicas tradicionales de procesado. En este sentido, una de las principales líneas de investigación persigue el objetivo del tiempo real mediante la paralelización del procesamiento, dividiendo esta carga computacional en varios núcleos que trabajen simultáneamente. A este respecto, en el presente documento se describe el desarrollo de una librería de procesado hiperespectral para el lenguaje RVC - CAL, que está específicamente pensado para el desarrollo de aplicaciones multimedia y proporciona las herramientas necesarias para paralelizar las aplicaciones. En concreto, en este Proyecto Fin de Grado se han desarrollado las funciones necesarias para implementar dos de las cuatro fases de la cadena de análisis de una imagen hiperespectral - en concreto, las fases de estimación del número de endmembers y de la estimación de la distribución de los mismos en la imagen -; conviene destacar que este trabajo se complementa con el realizado por Daniel Madroñal en su Proyecto Fin de Grado, donde desarrolla las funciones necesarias para completar las otras dos fases de la cadena. El presente documento sigue la estructura clásica de un trabajo de investigación, exponiendo, en primer lugar, las motivaciones que han cimentado este Proyecto Fin de Grado y los objetivos que se esperan alcanzar con él. A continuación, se realiza un amplio análisis del estado del arte de las tecnologías necesarias para su desarrollo, explicando, por un lado, las imágenes hiperespectrales y, por otro, todos los recursos hardware y software necesarios para la implementación de la librería. De esta forma, se proporcionarán todos los conceptos técnicos necesarios para el correcto seguimiento de este documento. Tras ello, se detallará la metodología seguida para la generación de la mencionada librería, así como el proceso de implementación de una cadena completa de procesado de imágenes hiperespectrales que permita la evaluación tanto de la bondad de la librería como del tiempo necesario para analizar una imagen hiperespectral completa. Una vez expuesta la metodología utilizada, se analizarán en detalle los resultados obtenidos en las pruebas realizadas; en primer lugar, se explicarán los resultados individuales extraídos del análisis de las dos etapas implementadas y, posteriormente, se discutirán los arrojados por el análisis de la ejecución de la cadena completa, tanto en uno como en varios núcleos. Por último, como resultado de este estudio se extraen una serie de conclusiones, que engloban aspectos como bondad de resultados, tiempos de ejecución y consumo de recursos; asimismo, se proponen una serie de líneas futuras de actuación con las que se podría continuar y complementar la investigación desarrollada en este documento. ABSTRACT. Hyperspectral imaging collects information from across the electromagnetic spectrum, covering a wide range of wavelengths. Although this technology was initially developed for remote sensing and earth observation, its multiple advantages - such as high spectral resolution - led to its application in other fields, as cancer detection. However, this new field has shown specific requirements; for example, it needs to accomplish strong time specifications, since all the potential applications - like surgical guidance or in vivo tumor detection - imply real-time requisites. Achieving this time requirements is a great challenge, as hyperspectral images generate extremely high volumes of data to process. For that reason, some new research lines are studying new processing techniques, and the most relevant ones are related to system parallelization: in order to reduce the computational load, this solution executes image analysis in several processors simultaneously; in that way, this computational load is divided among the different cores, and real-time specifications can be accomplished. This document describes the construction of a new hyperspectral processing library for RVC - CAL language, which is specifically designed for multimedia applications and allows multithreading compilation and system parallelization. This Diploma Project develops the required library functions to implement two of the four stages of the hyperspectral imaging processing chain - endmember and abundance estimations -. The two other stages - dimensionality reduction and endmember extraction - are studied in the Diploma Project of Daniel Madroñal, which complements the research work described in this document. The document follows the classical structure of a research work. Firstly, it introduces the motivations that have inspired this Diploma Project and the main objectives to achieve. After that, it thoroughly studies the state of the art of the technologies related to the development of the library. The state of the art contains all the concepts needed to understand the contents of this research work, like the definition and applications of hyperspectral imaging and the typical processing chain. Thirdly, it explains the methodology of the library implementation, as well as the construction of a complete processing chain in RVC - CAL applying the mentioned library. This chain will test both the correct behavior of the library and the time requirements for the complete analysis of one hyperspectral image, either executing the chain in one processor or in several ones. Afterwards, the collected results will be carefully analyzed: first of all, individual results -from endmember and abundance estimations stages - will be discussed and, after that, complete results will be studied; this results will be obtained from the complete processing chain, so they will analyze the effects of multithreading and system parallelization on the mentioned processing chain. Finally, as a result of this discussion, some conclusions will be gathered regarding some relevant aspects, such as algorithm behavior, execution times and processing performance. Likewise, this document will conclude with the proposal of some future research lines that could continue the research work described in this document.