146 research outputs found
3D measurements in conventional X-ray imaging with RGB-D sensors
No full text[EN] A method for deriving 3D internal information in conventional X-ray settings is presented. It is based on the combination of a pair of radiographs from a patient and it avoids the use of X-ray-opaque fiducials and external reference structures. To achieve this goal, we augment an ordinary X-ray device with a consumer RGB-D camera. The patient' s rotation around the craniocaudal axis is tracked relative to this camera thanks to the depth information provided and the application of a modern surface-mapping algorithm. The measured spatial information is then translated to the reference frame of the X-ray imaging system. By using the intrinsic parameters of the diagnostic equipment, epipolar geometry, and X-ray images of the patient at different angles, 3D internal positions can be obtained. Both the RGB-D and Xray instruments are first geometrically calibrated to find their joint spatial transformation. The proposed method is applied to three rotating phantoms. The first two consist of an anthropomorphic head and a torso, which are filled with spherical lead bearings at precise locations. The third one is made of simple foam and has metal needles of several known lengths embedded in it. The results show that it is possible to resolve anatomical positions and lengths with a millimetric level of precision. With the proposed approach, internal 3D reconstructed coordinates and distances can be provided to the physician. It also contributes to reducing the invasiveness of ordinary X-ray environments and can replace other types of clinical explorations that are mainly aimed at measuring or geometrically relating elements that are present inside the patient's body.(C) 2017 IPEM. Published by Elsevier Ltd. All rights reserved.The authors would like to thank the Radiation Oncology Department of the Physics Section at La Fe Hospital for the anthropomorphic phantom used in this work and Jose Manuel Monserrate (Instituto de Física Corpuscular) for his contribution in the development of the calibration frame shown in Fig. 3. This research has the support of Information Storage S.L., University of Valencia (grant CPI-15-170), CSD-2007-00042 Con solider Ingenio CPAN (grant CPAN-13TR01), IFIC (Severo Ochoa Centre of Excellence SEV20140398) as well as the support of the Spanish Ministry of Industry, Energy, and Tourism (grant TSI1001012013019).Albiol Colomer, F.; Corbi, A.; Albiol Colomer, A. (2017). 3D measurements in conventional X-ray imaging with RGB-D sensors. Medical Engineering & Physics. 42:73-79. https://doi.org/10.1016/j.medengphy.2017.01.024S73794
Geometrical Calibration of X-Ray Imaging With RGB Cameras for 3D Reconstruction
No full text(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.We present a methodology to recover the geometrical calibration of conventional X-ray settings with the help of an ordinary video camera and visible fiducials that are present in the scene. After calibration, equivalent points of interest can be easily identifiable with the help of the epipolar geometry. The same procedure also allows the measurement of real anatomic lengths and angles and obtains accurate 3D locations from image points. Our approach completely eliminates the need for X-ray-opaque reference marks (and necessary supporting frames) which can sometimes be invasive for the patient, occlude the radiographic picture, and end up projected outside the imaging sensor area in oblique protocols. Two possible frameworks are envisioned: a spatially shifting X-ray anode around the patient/object and a moving patient that moves/rotates while the imaging system remains fixed. As a proof of concept, experiences with a device under test (DUT), an anthropomorphic phantom and a real brachytherapy session have been carried out. The results show that it is possible to identify common points with a proper level of accuracy and retrieve three-dimensional locations, lengths and shapes with a millimetric level of precision. The presented approach is simple and compatible with both current and legacy widespread diagnostic X-ray imaging deployments and it can represent a good and inexpensive alternative to other radiological modalities like CT.This work was carried out with the support of Information Storage S.L., University of Valencia (grant #CPI-15-170), CSD2007-00042 Consolider Ingenio CPAN (grant #CPAN13-TR01) as well as with the support of the Spanish Ministry of Industry, Energy and Tourism (Grant TSI-100101-2013-019).Albiol Colomer, F.; Corbi, A.; Albiol Colomer, A. (2016). Geometrical Calibration of X-Ray Imaging With RGB Cameras for 3D Reconstruction. IEEE Transactions on Medical Imaging. 35(8):1952-1961. https://doi.org/10.1109/TMI.2016.2540929S1952196135
Circadian variations of short-term heart period irreversibility in healthy and chronic heart failure patients
No full textWe exploited time irreversibility analysis to characterize short heart period sequences (256 samples) derived from 24h Holter recordings in normal healthy (NO) subjects and chronic heart failure (CHF) patients. We found a significant presence of irreversible dynamics over short time scales, whereas over dominant, longer time scales irreversibility was marginal. Over short time scales in NO subjects the percentage of irreversible dynamics was larger during daytime than during nighttime, thus indicating a larger presence of non linear dynamics during daytime. Same circadian variation was detected in CHF patients but the percentage of irreversible series was higher. In NO subjects during daytime the non linear behavior was mostly the result of bradycardic runs shorter than tachycardic ones. In CHF population this pattern was as present as the reverse pattern (i.e. tachycardic runs shorter than bradycardic ones). Time irreversibility analysis provides useful and reliable indexes even in uncontrolled experimental conditions and during daily activities
Environment recognition applied to particle detectors
No full textIn contrast with other radiological modalities (such as the computer- ized axial tomography or CT) and well-defined experimental setups related to nuclear physics and particle tracking (gamma detectors, accelerators, etc.), many radiation detection devices or imaging systems (i.e., those used in medical imaging and/or radiation protection) do not take into account the geometrical information concerning the scene in which they operate. The main goal of this thesis work is the development of the nec- essary methods and techniques to provide this information to whichever detection device is used and, in a general way. This augmentation (con- cept borrowed from the world of computer vision) is achieved through the interplay of an external environment recognition device.
In the context of this thesis work, a scene or environment entails, not only the outline of the location, room or surroundings where any sort of photon intensity measurements or imaging process takes place, but also the proper element under examination (person, contaminated object, radioactive source, etc.), including its/his/her position, orientation and volume relative to the imaging system or a fixed point in space. That is the case of general purpose X-ray imaging equipment or portable radia- tion measurement devices used to evaluate, for instance, environmental γ or β emissions. As it is demonstrated in this work, the aforementioned scene’s geometry can complement o augment, in a very significant way, the inherent information obtained by these imaging systems. Similarly, in the scope of this research project, a device A augments another device B when A provides B with accurate spatial references, allowing for instance, 3D reconstruction for B, A+B image overlay (registration), image stitching for B, etc.
In order to achieve the aforementioned goal, some methods and tech- niques around the determination of the spatial setting have been tested and explored within the following areas of application:
• augmentation of primary care X-ray imaging systems,
• three-dimensional reconstruction of a the anatomy of the patient under examination using ordinary radiographs,
• derivation of new transfer functions that enable the generation of densitometric images from X-ray absorption ones and the patient’s volume,
• assessment of 3D coordinates to radioactive sources and the received dose.
The present research mainly focuses on the augmentation of conventional X-ray imaging systems through the interplay of an external positioning or scene-delimitation device (i.e., a video camera, depth sensor, etc.) like the one shown in the image above. Nevertheless, other particle detection systems (i.e., γ cameras) are also explored. The main advantage of a dual-camera assembly is the possibility of geometrically determining the radiographic (or radioactive) scene with accuracy and being able to map both types of information.
In the context of medical imaging, the reason for choosing this specific equipment type (general purpose X-rays) is their undeniable presence, not only in healthcare, but also industrial domains. The quantification of the available geometrical information surrounding ordinary X-ray examina- tion rooms opens many interesting possibilities which were so far limited to more complex radiological modalities such as CT scanners (i.e., anatom- ical 3D reconstruction). In contrast with tomographies and as highlighted in Chapter 3, the geometry derived in conventional X-ray imaging can be very variable from session to session and is very rarely (or never) registered, stored or taken into account during the imaging process. More specifically, in this thesis work, we begin by establishing methods and materials (in- volving the use of the aforementioned external environment recognition devices) to account for this, so far ignored, scene geometry. This infor- mation will later allow us to derive 3D relations from plain radiographs, which is discussed in Chapter 4 and Chapter 5. These 3D reconstruction capabilities are in turn based on an earlier geometrical calibration phase of the imaging system, examined in Chapter 3.
In Chapter 6 we present a technique to obtain densitometric X-ray images from plain radiographs in combination with the patient’s volume. The foundations of this technique rely on the theoretical and practical background developed in previous chapters. Next, in Chapter 7 we present some experiments and tests carried out with anthropomorphic phantoms and patients in real clinical setups around the techniques and procedures introduced in this document. In Appendix A, we outline a novel method- ology to assess the quality of X-ray images. This metric will enable the objective assessment of the amount of information contained in conven- tional radiographs and compare it against the new density-based ones.
As stated above, the concept of environment recognition is also ap- plied to particle detectors, notably portable γ-ray cameras. This scope of application is addressed in Chapter 8, where similar steps, methods and tools to those previously applied in the augmentation of X-ray imaging scenarios are now implemented to radiation detection in nuclear waste management locations. Finally, we will also address new approaches for dose assessment based on the measured target’s volume.Resumen en español
Introducción
Los detectores de partículas son dispositivos que registran la radiación ionizante, bien de sistemas activos (rayos X, aceleradores, etc.) o bien de isótopos radiactivos. Para poder realizar medidas de precisión con estos instrumentos, es necesario modelar geométricamente el entorno, contorno o escena bajo estudio. Estas condiciones geométricas se pueden determinar de forma más o menos precisa en algunos experimentos de física de partículas/nuclear, y en algunos sistemas de imagen, como las tomografías. Sin embargo, este escenario no es necesariamente el habitual. El propósito principal de este trabajo de tesis es desarrollar técnicas e instrumentos que aporten la mencionada información del entorno a cualquier sistema de detección de radiación y de manera general. Como iremos viendo, estas mejoras tienen lugar mediante la adición de sensores externos (cámaras de video y cámaras de rango, principalmente) capaces de aportar dichos datos sobre el contexto espacial.
Por escena o contorno se entiende tanto los límites del emplazamiento físico donde se realizan las medidas (habitación, habitáculo, recinto, alrededores, etc.), como el propio elemento bajo examen (paciente, objeto contaminado, fuente radioactiva, etc.), incluyendo su posición, giro y volumen relativo al sistema de imagen o a un punto fijo. Tal es el caso de los dispositivos de rayos X de propósito general o los sistemas detectores portátiles usados, por ejemplo, para la medición de radiación ambiental. Como se demuestra a lo largo de este trabajo de tesis, la mencionada geometría de la escena puede llegar a complementar o aumentar (concepto tomado prestado del mundo de la visión por ordenador o computer vision) de manera muy significativa la información propia recabada por los sistemas de adquisición utilizados. De manera similar, cuando un dispositivo A aumenta un dispositivo B, implica que A provee a B con información espacial relativa a marco de trabajo, de manera que puede derivarse, por ejemplo, información 3D por parte de B, registrar imágenes A+B, etc.
Para alcanzar este objetivo, y como parte de esta investigación, se han explorado técnicas y métodos de reconocimiento del entorno, aplicados a las siguientes áreas:
• aumento de dispositivos de rayos X usados en diagnóstico primario,
• reconstrucción tridimensional de la anatomía de la persona examinada partiendo de radiografías convencionales que luego pueden ser estereográficamente relacionadas,
• obtención de nuevas funciones de transferencia que permitan la generación de imágenes densitométricas a partir de las imágenes de absorción y el volumen del/de la paciente, y
• asignación de coordenadas 3D a fuentes de radiación y a la dosis recibida.
Se ha hecho especial énfasis en los dispositivos de rayos X por su indudable presencia en muchos ámbitos, desde los puramente clínicos hasta los relacionados con la inspección preventiva/forense de objetos. En el contexto de este trabajo, estos sistemas de imagen son aumentados mediante la interacción con dispositivos modernos de posicionamiento, tales como cámaras de video, profundidad, etc. La ventaja de esta arquitectura de imagen dual es la posibilidad de determinar geométricamente la escena con precisión y trasladar y superponer esta información al resultado de origen clínico (o al fruto de una inspección relacionada con la gestión de residuos radioactivos, como en el caso de las gamma-cámaras, estudiadas en [chap:gamma]).
Además, como parte de los resultados obtenidos en esta tesis, se ha desarrollado una métrica especial (basada en análisis y teoría de la imagen) para cuantificar de manera objetiva la calidad de imágenes radiográficas. Esta técnica es utilizada para estimar la información de las imágenes densitométricas obtenidas mediante los métodos estudiados en este trabajo.
Los rayos X convencionales y sus limitaciones
La modalidad radiológica de rayos X convencional es sin duda la más presente y usada en la práctica clínica y ciencias de la salud. Su implantación en todo tipo de centros de salud es muy destacable dada su relativa simplicidad técnica, rapidez y efectividad para diagnosticar muchos tipos de dolencias. La llegada de la radiografía digital no ha hecho otra cosa sino profundizar en esta realidad.
Un dispositivo de rayos X consta de un tubo generador de este tipo de radiación instalado dentro de un blindaje, un generador de alta tensión y un chasis o cassette que contiene en su interior la película radiográfica o detector digital que integra finalmente la emisión Roentgen que no ha sido absorbida por el/la paciente o el objeto analizado.
A diferencia de otras modalidades como la tomografía axial computerizada (TAC), en la modalidad de rayos X ordinarios la geometría de la escena clínica es descrita de manera muy somera. Con enorme frecuencia, el único registro de la misma son sencillas indicaciones relativas a la posición (y sobre todo, orientación) del/de la paciente con respecto a la cubierta protectora del detector de pared vertical y/o mesa horizontal. Es lo que se conoce en literatura como protocolo o simplemente, posicionamiento del paciente. Estas indicaciones son las que luego se traducen en los conocidos protocolos de examen tales como radiografía postero-anterior, antero-posterior, decúbito, medio-lateral, etc. Esta alta variabilidad geométrica proviene del hecho de que en los dispositivos de rayos X para diagnóstico primario existe un desacoplo estructural entre el detector y la fuente de fotones X (el ánodo del tubo). Dicho de otra manera: ambos pueden desplazarse libremente y con plena independencia el uno del otro. Esto se traduce a su vez en una alta fragilidad de los parámetros intrínsecos (a diferencia de una cámara fotográfica al uso, donde estos valores permanecen fijos desde el momento de su fabricación). Tanto las mesas de examen como los estativos verticales pueden ser fijos, flotantes o semi-flotantes e incluso a veces es posible modificar su ángulo con respecto al suelo o pared para realizar exámenes especiales, como los digestivos. En cualquier sistema de imagen, los parámetros intrínsecos engloban tanto el punto focal como posibles distorsiones y asimetrías que pueden ser medidas y conocidas.
Un ejemplo que suele resultar llamativo de esta libertad de movimiento en los sistemas de imagen por rayos X es el hecho de que el punto focal (distancia desde el ánodo al detector y su posición horizontal y vertical en el plano representado por este) puede llegar a estar situado completamente fuera de la superficie de la imagen. Esto acontece, por ejemplo, en algunos protocolos que exigen proyecciones oblicuas o en ángulos muy picados (como las que se muestran en la [fig:xraypositions] y la [fig:oblique]). Nuevamente, esta situación contrasta con la fotografía convencional, donde el punto principal se corresponde normalmente con el pixel central, por ejemplo, en el 640, 540 en el caso de una cámara de video de resolución HD (1920, 1080). Los proyectores de luz (usados comúnmente en presentaciones, arte, etc.) también emplean un punto focal muy desplazado con respecto al centro de la imagen, sin embargo esta sólo se forma con nitidez a una distancia específica y fija (es decir, los parámetros intrínsecos del sistema óptico son nuevamente fijos).
Si bien es cierto que la tecnología y estándares radiológicos están preparados para el registro de ciertas distancias tales como la brecha paciente-detector (IOD), emisor-detector (SID), etc., estas casi nunca son estimadas, ni medidas y mucho menos inventariadas manual o electrónicamente. Sin embargo, es bien conocido tanto teórica como experimentalmente, así como por la práctica diaria, que estas magnitudes pueden llegar a tener una repercusión no despreciable tanto en la generación de la propia imagen radiográfica y su calidad, así como en la gestión de la dosis recibida por parte del/de la paciente.
Rayos-X aumentados mediante dispositivos de captación de contorno
En este trabajo proponemos una serie de herramientas, metodologías y procedimientos para la determinación del ámbito geométrico en escenarios de diagnóstico basados en sistemas convencionales de rayos X. Estas técnicas se apoyan principalmente en la anexión de un dispositivo de captación de contorno o escena que permanece rígidamente acoplado al sistema de imagen de rayos X. Los dispositivos de captación de contorno que han sido explorados en este trabajo son cámaras de video y cámaras de profundidad, aunque existen muchas otras alternativas tales como cámaras basadas en tiempo de vuelo (time-of-flight), LIDARes (light detection and ranging), escáneres 3D láser, sistemas de visión estereoscópica con cámaras RGB calibradas, etc. Una cámara calibrada (sea del tipo que sea: RGB, profundidad, rayos-X) es aquella de la que se conocen sus parámetros intrínsecos y posición respecto a un punto de referencia externo llamado usualmente mundo.
Mediante estas cámaras adyacentes y anexionadas de manera rígida es posible la delimitación geométrica de la escena de rayos X, incluidas las distancias anteriormente mencionadas, además de la posición precisa del/de la paciente durante el examen y su volumen. Además, en combinación con una segunda (o más) radiografía(s), es posible aplicar técnicas de estereoscopía y reconstrucción 3D y obtener información tridimensional de su anatomía interna, además de otros valiosos datos válidos para complementar el diagnóstico.
En la última década ha acontecido una revolución tecnológica en relación a los dispositivos de captación de contorno, dando lugar a nuevas disciplinas tales como la detección remota, la realidad virtual o la realidad aumentada. Estos nuevos instrumentos conllevan ventajas a las que ya nos hemos ido acostumbrando y se han convertido incluso en cotidianas, tales como la estimación remota de distancias y posiciones, el cálculo de coordenadas, el modelado de superficies, el seguimiento de personas y objetos, la detección barreras y obstáculos, la cartografía y posicionamiento geográfico, entre muchas otras. Los ámbitos de aplicación de los saberes relacionados con la visión por ordenador están ahora al alcance de muchas disciplinas que hasta hace poco se auto-excluían de tales dominios tecnológicos. Entre estas ciencias podemos encontrar a la medicina, la física y otras ciencias básicas.
En lo que concierte a los rayos X, cierto tipo de información geométrica y proyectiva (a excepción del volumen del objeto o persona radiografiada) estaba ya disponible gracias a la intercesión de incómodos y costosos marcos de referencia que contienen marcadores fiduciarios opacos a la radiación Roentgen. Esta metodología heredada (así como sus sucesoras basadas en detectores de contorno que se proponen en este trabajo) radica en el hecho de que un dispositivo de rayos X puede asemejarse a una cámara pinhole o cámara estenopeica. Una cámara estenopeica es una cámara fotográfica sin lente y que cuenta con un pequeño orificio o pinhole por donde entra la luz reflejada por los objetos fotografiados, además un material detector. En el caso de un dispositivo de rayos X, el pinhole es en realidad el emisor de luz y coincide estructuralmente con el ánodo del tubo de rayos X, que juega también el papel del anteriormente citado punto focal.
El detector en los dispositivos de rayos X estenopeicos es la placa radiográfica o el imaging plate (en el caso digital). La geometría proyectiva afirma que dados conjuntos de puntos con coordenadas espaciales (3D) y sus correspondientes proyecciones en una imagen, es posible hallar la ecuación de calibración de cámara que conecta cualquier otro punto tridimensional en la escena con su localización x,\,y en la imagen. Es lo que se conoce también con el nombre de calibración geométrica de cámara.
El problema con la solución basada en marcos de referencia y fiduciales opacas nombrada anteriormente es que pueden dificultar la movilidad del/de la paciente y/o del sistema, pero sobretodo pueden alterar de manera significativa la imagen e influir en el diagnóstico alcanzable a partir de la misma. En el [chap:xraycalibration] se estudian y comparan los distintos algoritmos de calibración de cámara pero aplicados al ámbito de los rayos X. Las técnicas propuestas en este trabajo evitan las mencionadas incomodidades para el/la paciente y no interfieren en absoluto en la generación de la placa radiográfica ni en la imagen de absorción final, además de otras ventajas, tales como la posibilidad de guardar registro visual de la escena, adquirir el contorno del/de la paciente o de aplicar protocolos de examen que requieran una gran oblicuidad por parte del sistema de adquisición.
Para combinar geométricamente ambos tipos de dispositivos (sensor de contorno y rayos X) es necesario encontrar con antelación la transformación rígida que los conecta, también conocida como ecuación de la co-cámara. Una transformación rígida es una transformación lineal que preserva tamaño y forma, conservando la alineación, el orden y la pertenencia (es decir, las rectas se transforman en rectas y ángulos en ángulos). La búsqueda de esta relación geométrica se detalla en la [sec:calibration-phase] y la [sec:calibration] para el caso de cámaras de visible y de profundidad, respectivamente. En esta fase (y sólo en esta) nos apoyamos en un marco de calibración que incorpora fiduciales detectables por ambos sistemas de imagen ([fig:calibrationframe]). Una vez hallada esta matriz de transformación, se dice que ambas cámaras están registradas. Tanto en el caso de que la cámara de contorno sea una cámara de video o de profundidad, los marcadores que aparecen en la proyección resultante son fácilmente identificables mediante herramientas de computer vision resumidas en la [sec:tracking]. En el caso de las proyecciones de marcadores opacos a los rayos X, estas son aisladas normalmente de manera manual, aunque es posible aplicar algoritmos de identificación de formas y segmentación sobre la radiografía de calibración. En este trabajo se ha optado por lo primero, aprovechando las mismas herramientas software de visualización y diagnóstico del médico-radiólogo. El proceso de hallazgo de la ecuación co-cámara se relata en la [sec:problem].
Reconstrucción 3D en rayos X
Una vez hallada esta relación de registro entre dispositivos, ya no es necesario el marco de calibración, el cual desaparece de la escena sin perjuicio ni influencia alguna en la(s) radiografía(s) del/de la paciente tal y como se ha anticipado en el párrafo anterior. A partir de este momento, es el detector de contorno el responsable de inferir la geometría de la escena, liberando completamente al sistema de rayos X de esta tarea. Entre los elementos propios de la geometría de la escena que son ahora cómodamente medibles se encuentran, por descontado, las longitudes listadas anteriormente (IOD, SID, etc.). Sin embargo, es posible además inferir otras entidades importantes, tales como el volumen del/de la paciente, sus desplazamientos y los movimientos propios del sistema radiológico entre radiografías consecutivas.
Concretamente, gracias a esta última ventaja (determinación de transformaciones rígidas entre dos desplazamientos) es posible reconstruir tridimensionalmente puntos y distancias internos al/a la paciente mediante técnicas de visión estereoscópica. Para ello sólo son necesarias dos radiografías obtenidas en dos posiciones separadas, ya sea del propio/de la propia paciente o del sistema radiográfico. Esta versatilidad relacionada con los escenarios de aplicación es tratada en la [sec:scenarios]. Este seguimiento o tracking de la escena es el que se detalla en el [chap:xray+rgb] y el [chap:kinfu] para el caso de que el sensor de contorno sea una cámara RGB y para el caso de una cámara de profundidad, respectivamente. Las cámaras de profundidad consisten en sistemas integrados por una luz láser que es proyectada, formando un patrón conocido, sobre la escena. El reflejo de este patrón es vuelto a ser captado por un sensor CMOS adjunto. A partir de la captura de la deformación del mencionado patrón, es posible determinar información 3D del entorno.
La información 3D obtenida por las cámaras de profundidad es transmitida a otros sistemas informáticos mediante las conocidas nubes de puntos o point clouds. Una nube de puntos es un conjunto de vértices en un sistema de coorde
X-ray imaging virtual online laboratory for engineering undergraduates
No full textDistance learning engineering students (as well as those in face-to-face settings) should acquire a basic background in radiation-matter interaction physics (usually in the first semesters). Some students in this group may feel some degree of aversion towards these types of pure science-related subjects (mathematics, physics, chemistry, etc). In online learning scenarios, the average student is already an adult (37 years old or above) and may see no particular application of the aforementioned courses in their current or future professional life. Besides this, online institutions tend to lean too much on applet-based simulations. Although they may shed some light on the theory associated with the studied physical processes, these animated and interactive examples also seem to be ' stripped down' versions of the real events, and are felt to be disconnected from current scientific environments and engineering settings. For this reason, we describe a novel virtual lab approach to teach the basics of the low-energy interactions present in average x-ray settings. It combines real scientific simulation frameworks with modern computing techniques such as virtualization, cloud infrastructures, containers, networking and shared collaboration environments. It also fosters the use of hugely demanded development tools and programming languages and addresses the fundamentals of digital radiography and the linked electronic standards for image storage and transmission. With this mixed approach, blending scientific concepts, healthcare and state-of-the-art software solutions, our virtual labs have proven (over a period of five academic terms) to be both very attractive to and pedagogically successful (technically, and scientifically) for online engineering undergraduates. For the sake of completeness, we also propose a hands-on activity that mimics the geometrical peculiarities of x-ray rooms with the help of visible light and cheap materials.Peer reviewe
Alberto Manzi traduttore di classici presso l'editrice La Scuola: la sfida della lettura per superare le povertà educative
No full textNel 1955, la scuola elementare è interessata dai Programmi Ermini volti ad "assicurare alla totalità dei cittadini quella formazione basilare della intelligenza e del carattere, che è condizione per un'effettiva e consapevole partecipazione alla vita della società e dello Stato" (DPR 14 giugno 1955, n.503). Questa partecipazione consapevole è un obiettivo importante per le nuove generazioni, e gli anni Cinquanta del Novecento segnano ancora un livello di analfabetismo e semianalfabetismo elevato. Tra gli autori per ragazzi di questo periodo, Alberto Manzi è scrittore poliedrico impegnato a combattere la povertà educativa che affliggeva l'Italia interessata da un'ondata di cambiamenti sociali, economici, formativi. Poco prima della fortunata trasmissione RAI "Non è mai troppo tardi" (1960-1968), Manzi collabora con la casa editrice La Scuola per la traduzione e riduzione di alcuni classici moderni. Nel materiale archivistico della casa editrice La Scuola conservato presso l'Università Cattolica del Sacro Cuore di Brescia è possibile tracciare le origini di questa collaborazione, inserita in un'attività di ampio respiro della casa editrice con la creazione di Collane di “carattere culturale, pedagogico, educativo, scolastico e professionale” tra le quali si annoverano iniziative volte ai giovani lettori. Manzi si era imposto all'attenzione della casa editrice con un suo manoscritto, rifiutato per la pubblicazione, già nel 1953. Tuttavia, la possibilità di sfruttare le capacità narrative del Manzi non viene meno e La Scuola gli propone un lavoro di traduzione e riduzione di alcuni autori stranieri che sfocerà nella prima pubblicazione di Kipling con i "Libri della giungla" e "Storie proprio così" (1957). Manzi procede con la riduzione di Stevenson e Cummins (quest'ultima con" Il lampionaio", già pubblicato da Sonzogno nel 1895), ma la casa editrice preferisce sostituire Cummins con un autore in linea con la rapidità narrativa del Manzi: si tratta di Verne e "Il giro del mondo in 80 giorni", pubblicato nel 1960. Nell'ottica di formazione alla lettura e critica traduttiva, è interessante la riduzione di Stevenson, della quale si intendono indagare le intenzioni di riscrittura alla base del lavoro, incrociando il carteggio tra Manzi e la casa editrice ed il testo poi pubblicato nel 1959. Su sollecitazione degli uffici preposti alla revisione del manoscritto, Manzi giustifica con occhio critico le sue scelte traduttive e di selezione del materiale, dalle quali si può cogliere sia la fedeltà verso l' autore (definita da Nord con il termine "loyalty") sia verso il lettore nel rapporto di coinvolgimento che si instaura nell’atto del leggere. Un'analisi puntuale della riduzione da Stevenson, quindi, può offrire spunti interessanti che coinvolgono non solo l'evidenza del testo ma anche la rete di relazioni tra traduttore e revisori in un contesto storico particolarmente attivo per la casa editrice
ELDER ABUSE AND VIOLENCE: SURVEY REGARDING LEVEL OF AWARENESS OF THIS PHENOMENON BY HEALTHCARE WORKERS FROM TWO ITALIAN HOSPITALS
No full textAfter attending this presentation, attendees will more fully appreciate the importance of knowing how to recognize the
various signs of elder abuse and the need to take the necessary steps both in prevention and in response.
This presentation will impact the forensic science community by demonstrating that elder abuse comes in many forms,
some obvious and others not so obvious. New ways to address this phenomenon must be formulated and put into practice.
Background: Elder abuse is a widespread but underestimated problem. The full extent of this difficult situation is not
known due to a lack of reports and/or complaints, as well as the difficulty in identifying the early warning signs of abuse. Many
forms of elder abuse exist and are psychological, economic, sexual, physical, social, and institutional in nature; however, abuse
also includes neglect and abandonment. It is clear that maltreatment may arise not only through active behavior, but also through
omissive behavior such as silence, underestimation, and failure to report. Knowing how to identify the characteristic signs of elder
abuse is the duty of every healthcare worker and is crucial in the adoption of suitable defense measures to protect the victim as well
as in dealing with the offender.1,2
Objective: To establish the level of awareness of this issue by healthcare workers and to understand if they are able to
promptly identify the early signs of abuse and take the necessary actions to report them.
Materials and Methods: From April 1 - 30, 2015, all employees (i.e., physicians, specializing physicians in training,
nurses, office support staff, social-healthcare workers, and orderlies) from the Internal Medicine Operating Unit and the Geriatrics
Department at Cardelli Hospital in Campobasso (Molise) and from the Policlinico of the University of Bari “Aldo Moro” (Puglia)
answered a questionnaire that was formulated by utilizing the provisions of other duly used and validated questionnaires from other
international situations that are used to explore: (1) employees’ awareness of the phenomenon; (2) employees’ ability to recognize
possible signs of abuse; (3) the prevalence of the phenomenon; and, (4) employees’ awareness regarding the proper actions to take
when they encounter a case of abuse.
Results: Data collection resulted in a total of 98 questionnaires administered to 142 respondents (69.0%). The majority
of questionnaires were completed by females (75.5%) between the ages of 41 and 50 years of age (26.7%) and by qualified
nurses (46.9%). Table 1 describes the preliminary data obtained and is broken down by unit and title of those who filled out the
questionnaire. Table 2 shows distribution by sex and the age range of compilers according to the operating unit to which they
belong.
Table 1
BARI (Puglia) CAMPOBASSO (Molise)
Internal Medicine Geriatrics Internal Medicine Geriatrics
Title Enrolled Collected Enrolled Collected Enrolled Collected Enrolled Collected
Physician 7 4 7 1 9 4 4 3
Physician in
training
15 11 15 14 0 0 0 0
Nurses 12 11 12 10 20 16 15 9
OSS 4 3 4 1 3 1 3 1
Orderlies 2 2 2 2 2 1 2 1
Aides 2 1 2 2 0 0 0 0
Total 42 32 42 30 34 22 24 14
Table 2
BARI (Puglia) CAMPOBASSO (Molise) Total
Internal Medicine Geriatrics Internal Medicine Geriatrics
Sex (M/F) 10/22 6/24 5/17 3/11 98
Age
21-30 10 10 4 0 24
31-40 8 5 6 2 21
41-50 7 8 4 8 27
>50 7 4 8 4 23
No response 0 3 0 0 3
877 *Presenting Author
Conclusions: These preliminary data show that interest in elder abuse, even when present, is neither a priority for all
healthcare workers nor is it perceived as a problem by them. This is probably due to a lack of knowledge about the phenomenon,
indicators of abuse, and the procedures to follow when one becomes aware of such an issue. As a result, a great need has been
identified for ongoing and updated training regarding more precise indicators of abuse and the procedures for the mandatory
reporting of this phenomenon to the health department and to judicial authorities.
Reference(s):
1. Corbi G., Grattagliano I., Catanesi R., Ferrara N., Yorston G., Campobasso C.P. Elderly residents at risk for being victims
or offenders. J Am Med Dir Assoc, 2012: 13(7), 657-9.
2. Corbi G.M., Grattagliano I., Ivshina E., Ferrara N., Solimeno C.A., Cmpobasso C.P. Elderly Abuse: Risk Factors And
Nursing Role. Intern Emerg Med, 2015 Apr;10(3):297-303
Elder Abuse, Elder Abuse Prevention, Elder Abuse Protoco
Connection between sleeping patterns and cognitive deterioration in women with Alzheimer’s disease
No full textBackground: Alzheimer’s disease (AD) causes symptoms such as dementia, memory loss, disorientation, and even aggressiveness, and is more common in women than in men. AD may also manifest itself in changes in sleep patterns. However, the relationship between AD (in all stages) and bedtime behavior has not been thoroughly investigated. Methods: In a prospective, cross-sectional survey, we evaluated 74 women categorized in two different stages of cognitive decline associated with AD (mild and severe) along with 37 women with no cognitive decline who served as controls. We obtained demographic and medical information such as age, health status, and medication, as well as psychiatrically confirmed staging of AD. We also collected actigraphy data for several nights in a row with a medical grade wristband using a 3-axis accelerometer and solid-state on-board memory. These data served as parameters for a clustering machine learning (ML) algorithm. Results: The ML process was able to unsupervisedly identify 85% of the participants according to their pre-assigned degree of dementia. When the clustering was carried out in a binary fashion (i.e., only taking into account healthy members vs. severely affected AD patients), it was possible to correctly classify 91% of the cases. Conclusions: This study revealed a strong connection between the severity of the intellectual decline and the features distilled from actigraphically derived sleep parameters. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG part of Springer Nature
ANTIOXIDANT SUPPLEMENTATION IN THE TREATMENT OF AGING-ASSOCIATED DISEASES
No full textOxidative stress is generally considered an imbalance between pro- and antioxidants species, which often results into indiscriminate and global damage at the organismal level. Elderly people are more susceptible to oxidative stress and this depends, almost in part, from a decreased performance of their endogenous antioxidant system. As many studies reported an inverse correlation between systemic levels of antioxidants and several diseases, primarily cardiovascular diseases, but also diabetes and neurological disorders, antioxidant supplementation has been foreseen as an effective preventive and therapeutic intervention for aging-associated pathologies. However, the expectations of this therapeutic approach have often been partially disappointed by clinical trials. The interplay of both endogenous and exogenous antioxidants with the systemic redox system is very complex and represents an issue that is still under debate. In this review a selection of recent clinical studies concerning antioxidants supplementation and the evaluation of their influence in aging-related diseases is analyzed. The controversial outcomes of the antioxidants supplementation therapy that might partially depend, among others, from an underestimation of the patient specific metabolic demand and genetic background, are presented
Automatic intensity windowing of mammographic images based on a perceptual metric
No full text[EN] Purpose: Initial auto-adjustment of the window level WL and width WW applied to mammographic images. The proposed intensity windowing (IW) method is based on the maximization of the mutual information (MI) between a perceptual decomposition of the original 12-bit sources and their screen displayed 8-bit version. Besides zoom, color inversion and panning operations, IW is the most commonly performed task in daily screening and has a direct impact on diagnosis and the time involved in the process.
Methods: The authors present a human visual system and perception-based algorithm named GRAIL (Gabor-relying adjustment of image levels). GRAIL initially measures a mammogram's quality based on the MI between the original instance and its Gabor-filtered derivations. From this point on, the algorithm performs an automatic intensity windowing process that outputs the WL/WW that best displays each mammogram for screening. GRAIL starts with the default, high contrast, wide dynamic range 12-bit data, and then maximizes the graphical information presented in ordinary 8-bit displays. Tests have been carried out with several mammogram databases. They comprise correlations and an ANOVA analysis with the manual IW levels established by a group of radiologists. A complete MATLAB implementation of GRAIL is available at .
Results: Auto-leveled images show superior quality both perceptually and objectively compared to their full intensity range and compared to the application of other common methods like global contrast stretching (GCS). The correlations between the human determined intensity values and the ones estimated by our method surpass that of GCS. The ANOVA analysis with the upper intensity thresholds also reveals a similar outcome. GRAIL has also proven to specially perform better with images that contain micro-calcifications and/or foreign X-ray-opaque elements and with healthy BI-RADS A-type mammograms. It can also speed up the initial screening time by a mean of 4.5 s per image.
Conclusions: A novel methodology is introduced that enables a quality-driven balancing of the WL/WW of mammographic images. This correction seeks the representation that maximizes the amount of graphical information contained in each image. The presented technique can contribute to the diagnosis and the overall efficiency of the breast screening session by suggesting, at the beginning, an optimal and customized windowing setting for each mammogram. (C) 2017 American Association of Physicists in MedicineThis work has the support of IST S.L., University of Valencia (CPI15170), Consolider (CPAN13TR01), MINETUR (TSI1001012013019) and IFIC (Severo Ochoa Centre of Excellence SEV20140398). The authors would also like to thank C. Bellot M.D., M. Brouzet M.D., C. Calabuig M.D., J. Camps M.D., J. Coloma M.D., D. Erades M.D., Mr. V. Gutierrez, J. Herrero M.D., Dr. I. Maestre, Dr. A. Neco M.D., C. Ortola M.D., A. Rubio M.D., Dr. R. Sanchez, Dr. F. Sellers, A. Segura M.D., and the Spanish Cancer Association (AECC) for their effort, participation, counseling, and commitment in this research study. The authors report no conflicts of interest in conducting the research.Albiol Colomer, A.; Corbi, A.; Albiol Colomer, F. (2017). Automatic intensity windowing of mammographic images based on a perceptual metric. Medical Physics. 44(4):1369-1378. https://doi.org/10.1002/mp.12144S13691378444Maidment, A. D. A., Fahrig, R., & Yaffe, M. J. (1993). Dynamic range requirements in digital mammography. Medical Physics, 20(6), 1621-1633. doi:10.1118/1.596949Kimpe, T., & Tuytschaever, T. (2006). Increasing the Number of Gray Shades in Medical Display Systems—How Much is Enough? Journal of Digital Imaging, 20(4), 422-432. doi:10.1007/s10278-006-1052-3ACR, AAPM, and SIIM Practice parameter for determinants of image quality in digital mammography 2014Committee DS PS3.3 information object definitions 2015Pisano, E. D., Chandramouli, J., Hemminger, B. M., Glueck, D., Johnston, R. E., Muller, K., … Pizer, S. (1997). The effect of intensity windowing on the detection of simulated masses embedded in dense portions of digitized mammograms in a laboratory setting. Journal of Digital Imaging, 10(4), 174-182. doi:10.1007/bf03168840Börjesson, S., Håkansson, M., Båth, M., Kheddache, S., Svensson, S., Tingberg, A., … Månsson, L. G. (2005). A software tool for increased efficiency in observer performance studies in radiology. Radiation Protection Dosimetry, 114(1-3), 45-52. doi:10.1093/rpd/nch550Sahidan, S. I., Mashor, M. Y., Wahab, A. S. W., Salleh, Z., & Ja’afar, H. (s. f.). Local and Global Contrast Stretching For Color Contrast Enhancement on Ziehl-Neelsen Tissue Section Slide Images. 4th Kuala Lumpur International Conference on Biomedical Engineering 2008, 583-586. doi:10.1007/978-3-540-69139-6_146Ganesan, K., Acharya, U. R., Chua, C. K., Min, L. C., Abraham, K. T., & Ng, K.-H. (2013). Computer-Aided Breast Cancer Detection Using Mammograms: A Review. IEEE Reviews in Biomedical Engineering, 6, 77-98. doi:10.1109/rbme.2012.2232289Papadopoulos, A., Fotiadis, D. I., & Costaridou, L. (2008). Improvement of microcalcification cluster detection in mammography utilizing image enhancement techniques. Computers in Biology and Medicine, 38(10), 1045-1055. doi:10.1016/j.compbiomed.2008.07.006Panetta, K., Yicong Zhou, Agaian, S., & Hongwei Jia. (2011). Nonlinear Unsharp Masking for Mammogram Enhancement. IEEE Transactions on Information Technology in Biomedicine, 15(6), 918-928. doi:10.1109/titb.2011.2164259Rogowska, J., Preston, K., & Sashin, D. (1988). Evaluation of digital unsharp masking and local contrast stretching as applied to chest radiographs. IEEE Transactions on Biomedical Engineering, 35(10), 817-827. doi:10.1109/10.7288Ramponi, G. (1998). Rational unsharp masking technique. Journal of Electronic Imaging, 7(2), 333. doi:10.1117/1.482649Rangayyan, R. M., Liang Shen, Yiping Shen, Desautels, J. E. L., Bryant, H., Terry, T. J., … Rose, M. S. (1997). Improvement of sensitivity of breast cancer diagnosis with adaptive neighborhood contrast enhancement of mammograms. IEEE Transactions on Information Technology in Biomedicine, 1(3), 161-170. doi:10.1109/4233.654859Tang, J., Liu, X., & Sun, Q. (2009). A Direct Image Contrast Enhancement Algorithm in the Wavelet Domain for Screening Mammograms. IEEE Journal of Selected Topics in Signal Processing, 3(1), 74-80. doi:10.1109/jstsp.2008.2011108LINGURARU, M., MARIAS, K., ENGLISH, R., & BRADY, M. (2006). A biologically inspired algorithm for microcalcification cluster detection. Medical Image Analysis, 10(6), 850-862. doi:10.1016/j.media.2006.07.004Tsai, D.-Y., Lee, Y., & Matsuyama, E. (2007). Information Entropy Measure for Evaluation of Image Quality. Journal of Digital Imaging, 21(3), 338-347. doi:10.1007/s10278-007-9044-5Sheikh, H. R., & Bovik, A. C. (2006). Image information and visual quality. IEEE Transactions on Image Processing, 15(2), 430-444. doi:10.1109/tip.2005.859378Tourassi, G. D., Vargas-Voracek, R., Catarious, D. M., & Floyd, C. E. (2003). Computer-assisted detection of mammographic masses: A template matching scheme based on mutual information. Medical Physics, 30(8), 2123-2130. doi:10.1118/1.1589494Tourassi, G. D., Harrawood, B., Singh, S., Lo, J. Y., & Floyd, C. E. (2006). Evaluation of information-theoretic similarity measures for content-based retrieval and detection of masses in mammograms. Medical Physics, 34(1), 140-150. doi:10.1118/1.2401667Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004). Image Quality Assessment: From Error Visibility to Structural Similarity. IEEE Transactions on Image Processing, 13(4), 600-612. doi:10.1109/tip.2003.819861Choi LK Goodall T Bovik AC Perceptual Image Enhancement. Encyclopedia of Image ProcessingFogel, I., & Sagi, D. (1989). Gabor filters as texture discriminator. Biological Cybernetics, 61(2). doi:10.1007/bf00204594Jain, A. K., Ratha, N. K., & Lakshmanan, S. (1997). Object detection using gabor filters. Pattern Recognition, 30(2), 295-309. doi:10.1016/s0031-3203(96)00068-4Vazquez-Fernandez, E., Dacal-Nieto, A., Martin, F., & Torres-Guijarro, S. (2010). Entropy of Gabor Filtering for Image Quality Assessment. Image Analysis and Recognition, 52-61. doi:10.1007/978-3-642-13772-3_6Rangayyan, R. M., Ayres, F. J., & Leo Desautels, J. E. (2007). A review of computer-aided diagnosis of breast cancer: Toward the detection of subtle signs. Journal of the Franklin Institute, 344(3-4), 312-348. doi:10.1016/j.jfranklin.2006.09.003Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., … Prior, F. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. Journal of Digital Imaging, 26(6), 1045-1057. doi:10.1007/s10278-013-9622-7Task Group 18 Imaging Informatics Subcommittee Assessment of display performance for medical imaging systems 2005A. C. of Radiology Committee Bi-rads atlas 5th edition 2014Hochberg, Y., & Benjamini, Y. (1990). More powerful procedures for multiple significance testing. Statistics in Medicine, 9(7), 811-818. doi:10.1002/sim.4780090710Keselman, H. J., & Keselman, J. C. (1984). The analysis of repeated measures designs in medical research. Statistics in Medicine, 3(2), 185-195. doi:10.1002/sim.4780030211Mauchly, J. W. (1940). Significance Test for Sphericity of a Normal -Variate Distribution. The Annals of Mathematical Statistics, 11(2), 204-209. doi:10.1214/aoms/1177731915Samei, E., Badano, A., Chakraborty, D., Compton, K., Cornelius, C., Corrigan, K., … Willis, C. E. (2005). Assessment of display performance for medical imaging systems: Executive summary of AAPM TG18 report. Medical Physics, 32(4), 1205-1225. doi:10.1118/1.1861159Haghighat, M., Zonouz, S., & Abdel-Mottaleb, M. (2015). CloudID: Trustworthy cloud-based and cross-enterprise biometric identification. Expert Systems with Applications, 42(21), 7905-7916. doi:10.1016/j.eswa.2015.06.02
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