A semi-automatic method for segmentation and 3D modeling of glioma tumors from brain MRI

This work presents an efficient method for volume rendering of glioma tumors from segmented 2D MRI Datasets with user interactive control, by replacing manual segmentation required in the state of art methods. The most common primary brain tumors are gliomas, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the pre- operative tumor volume is essential. Tumor portions were automatically segmented from 2D MR images using morphological filtering techniques. These seg- mented tumor slices were propagated and modeled with the software package. The 3D modeled tumor consists of gray level values of the original image with exact tumor boundary. Axial slices of FLAIR and T2 weighted images were used for extracting tumors. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming proc- ess and is prone to error. These defects are overcome in this method. Authors verified the performance of our method on several sets of MRI scans. The 3D modeling was also done using segmented 2D slices with the help of a medical software package called 3D DOCTOR for verification purposes. The results were validated with the ground truth models by the Radi- ologist.

Texture Description of low grade and high grade Glioma using Statistical features in Brain MRIs

Low grade and High grade Gliomas are tumors that originate in the glial cells. The main challenge in brain tumor diagnosis is whether a tumor is benign or malignant, primary or metastatic and low or high grade. Based on the patient's MRI, a radiologist could not differentiate whether it is a low grade Glioma or a high grade Glioma. Because both of these are almost visually similar, autopsy confirms the diagnosis of low grade with high-grade and infiltrative features. In this paper, textural description of Grade I and grade III Glioma are extracted using First order statistics and Gray Level Co-occurance Matrix Method (GLCM). Textural features are extracted from 16X16 sub image of the segmented Region of Interest(ROI) .In the proposed method, first order statistical features such as contrast, Intensity , Entropy, Kurtosis and spectral energy and GLCM features extracted were showed promising results. The ranges of these first order statistics and GLCM based features extracted are highly discriminant between grade I and Grade III. In this study which gives statistical textural information of grade I and grade III Glioma which is very useful for further classification and analysis and thus assisting Radiologist in greater extent.

Automatic Detection and Classification of Glioma Tumors using Statistical Features

The characterization and grading of glioma tumors, via image derived features, for diagnosis, prognosis, and treatment response has been an active research area in medical image computing. This paper presents a novel method for automatic detection and classification of glioma from conventional T2 weighted MR images. Automatic detection of the tumor was established using newly developed method called Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA).Statistical Features were extracted from the detected tumor texture using first order statistics and gray level co-occurrence matrix (GLCM) based second order statistical methods. Statistical significance of the features was determined by t-test and its corresponding p-value. A decision system was developed for the grade detection of glioma using these selected features and its p-value. The detection performance of the decision system was validated using the receiver operating characteristic (ROC) curve. The diagnosis and grading of glioma using this non-invasive method can contribute promising results in medical image computing

Statistical evaluation of texture analysis from the biocrystallization method

The consumers are becoming more concerned about food quality, especially regarding how, when and where the foods are produced (Haglund et al., 1999; Kahl et al., 2004; Alföldi, et al., 2006). Therefore, during recent years there has been a growing interest in the methods for food quality assessment, especially in the picture-development methods as a complement to traditional chemical analysis of single compounds (Kahl et al., 2006). The biocrystallization as one of the picture-developing method is based on the crystallographic phenomenon that when crystallizing aqueous solutions of dihydrate CuCl2 with adding of organic solutions, originating, e.g., from crop samples, biocrystallograms are generated with reproducible crystal patterns (Kleber & Steinike-Hartung, 1959). Its output is a crystal pattern on glass plates from which different variables (numbers) can be calculated by using image analysis. However, there is a lack of a standardized evaluation method to quantify the morphological features of the biocrystallogram image. Therefore, the main sakes of this research are (1) to optimize an existing statistical model in order to describe all the effects that contribute to the experiment, (2) to investigate the effect of image parameters on the texture analysis of the biocrystallogram images, i.e., region of interest (ROI), color transformation and histogram matching on samples from the project 020E170/F financed by the Federal Ministry of Food, Agriculture and Consumer Protection(BMELV).The samples are wheat and carrots from controlled field and farm trials, (3) to consider the strongest effect of texture parameter with the visual evaluation criteria that have been developed by a group of researcher (University of Kassel, Germany; Louis Bolk Institute (LBI), Netherlands and Biodynamic Research Association Denmark (BRAD), Denmark) in order to clarify how the relation of the texture parameter and visual characteristics on an image is. The refined statistical model was accomplished by using a lme model with repeated measurements via crossed effects, programmed in R (version 2.1.0). The validity of the F and P values is checked against the SAS program. While getting from the ANOVA the same F values, the P values are bigger in R because of the more conservative approach. The refined model is calculating more significant P values. The optimization of the image analysis is dealing with the following parameters: ROI(Region of Interest which is the area around the geometrical center), color transformation (calculation of the 1 dimensional gray level value out of the three dimensional color information of the scanned picture, which is necessary for the texture analysis), histogram matching (normalization of the histogram of the picture to enhance the contrast and to minimize the errors from lighting conditions). The samples were wheat from DOC trial with 4 field replicates for the years 2003 and 2005, “market samples”(organic and conventional neighbors with the same variety) for 2004 and 2005, carrot where the samples were obtained from the University of Kassel (2 varieties, 2 nitrogen treatments) for the years 2004, 2005, 2006 and “market samples” of carrot for the years 2004 and 2005. The criterion for the optimization was repeatability of the differentiation of the samples over the different harvest(years). For different samples different ROIs were found, which reflect the different pictures. The best color transformation that shows efficiently differentiation is relied on gray scale, i.e., equal color transformation. The second dimension of the color transformation only appeared in some years for the effect of color wavelength(hue) for carrot treated with different nitrate fertilizer levels. The best histogram matching is the Gaussian distribution. The approach was to find a connection between the variables from textural image analysis with the different visual criteria. The relation between the texture parameters and visual evaluation criteria was limited to the carrot samples, especially, as it could be well differentiated by the texture analysis. It was possible to connect groups of variables of the texture analysis with groups of criteria from the visual evaluation. These selected variables were able to differentiate the samples but not able to classify the samples according to the treatment. Contrarily, in case of visual criteria which describe the picture as a whole there is a classification in 80% of the sample cases possible. Herewith, it clearly can find the limits of the single variable approach of the image analysis (texture analysis).

Entwicklung eines Verfahrens zum Schneiden und Schälen von Obst mit Hochdruckwasserstrahlen

Im Rahmen der vorliegenden Arbeit wird ein Verfahren vorgestellt und untersucht, mit welchem Früchte annähernd verlustfrei und unter sehr hygienischen Bedingungen geschnitten werden können. Die Produkte – hier gezeigt am Beispiel von Äpfeln und Melonen – werden mit einem Hochdruckwasserstrahl geschnitten, der durch ein bildverarbeitendes System entsprechend der Anatomie der Frucht geführt werden kann. Die Vorteile dieses Verfahrens sind die individuelle Schnittführung, die Materialverluste minimiert und die Tatsache, dass die Frucht ohne wesentlichen Eingriff von Personal bearbeitet wird. Die Literaturauswertung ergab, dass diese Technologie bislang noch nicht bearbeitet wurde. Der Einsatz des Hochdruckwasserstrahlschneidens im Bereich der Agrartechnik beschränkte sich auf das Schneiden von Zuckerrüben Brüser [2008], Ligocki [2005] bzw. Kartoffeln Becker u. Gray [1992], das Zerteilen von Fleisch Bansal u. Walker [1999] und Fisch Lobash u. a. [1990] sowie die Nutzung von Wasserstrahlen im Zusammenhang mit der Injektion von Flüssigdünger in Ackerböden Niemoeller u. a. [2011]. Ziel dieser Arbeit war es daher, die Einsatzmöglichkeiten des Wasserstrahlschneidens zu erfassen und zu bewerten. Dazu wurden in einer Vielzahl von Einzelversuchen die Zusammenhänge zwischen den Prozessparametern wie Wasserdruck, Düsendurchmesser, Vorschubgeschwindigkeit und Düsenabstand auf das Schnittergebnis, also die Rauheit der entstehenden Schnittfläche untersucht. Ein Vergleich mit konventionellen Schneidemethoden erfolgte hinsichtlich der Schnittergebnisse und der Auswirkungen des Wasserstrahlschneidens auf nachfolgende Verfahrensschritte, wie dem Trocknen.

Skript Interprozesskommunikation

Das hier frei verfügbare Skript gehört zu einer gleichnamigen Vorlesung, die von Prof. Dr. Lutz Wegner bis zum Sommersemester 2007 gehalten wurde. Davor lief sie bis 1999 unter dem etwas irreführenden Titel „Ausgewählte Themen zu Rechnernetzen“. Behandelt wird die IPC in UNIX-basierten Rechnernetzen. Dazu gehören allgemeine Kenntnisse der Prozessumgebung, die fork- und exec-Systemaufrufe, Lock Files, Signale, Pipes, das Botschaftenkonzept (message queues), Semaphore, Shared Memory, Remote Procedure Calls, Sockets und Threads. Jedes Konzept wird mit kleinen Beispielen besprochen, die in C geschrieben sind. Der Quelltext liegt auf unseren Anlagen vor (für AIX, LINUX, Solaris). Grundlage der Vorlesung und des Skripts ist das ausgezeichnete Buch von John Shapley Gray „Interprocess Communications in UNIX“ aus dem Jahr 1998 bzw. die auf Linux angepasste Auflage desselben Buches „Interprocess Communications in LINUX“ aus dem Jahr 2003.

Compact Representations for Fast Nonrigid Registration of Medical Images

We develop efficient techniques for the non-rigid registration of medical images by using representations that adapt to the anatomy found in such images. Images of anatomical structures typically have uniform intensity interiors and smooth boundaries. We create methods to represent such regions compactly using tetrahedra. Unlike voxel-based representations, tetrahedra can accurately describe the expected smooth surfaces of medical objects. Furthermore, the interior of such objects can be represented using a small number of tetrahedra. Rather than describing a medical object using tens of thousands of voxels, our representations generally contain only a few thousand elements. Tetrahedra facilitate the creation of efficient non-rigid registration algorithms based on finite element methods (FEM). We create a fast, FEM-based method to non-rigidly register segmented anatomical structures from two subjects. Using our compact tetrahedral representations, this method generally requires less than one minute of processing time on a desktop PC. We also create a novel method for the non-rigid registration of gray scale images. To facilitate a fast method, we create a tetrahedral representation of a displacement field that automatically adapts to both the anatomy in an image and to the displacement field. The resulting algorithm has a computational cost that is dominated by the number of nodes in the mesh (about 10,000), rather than the number of voxels in an image (nearly 10,000,000). For many non-rigid registration problems, we can find a transformation from one image to another in five minutes. This speed is important as it allows use of the algorithm during surgery. We apply our algorithms to find correlations between the shape of anatomical structures and the presence of schizophrenia. We show that a study based on our representations outperforms studies based on other representations. We also use the results of our non-rigid registration algorithm as the basis of a segmentation algorithm. That algorithm also outperforms other methods in our tests, producing smoother segmentations and more accurately reproducing manual segmentations.

Rotation Invariant Real-time Face Detection and Recognition System

In this report, a face recognition system that is capable of detecting and recognizing frontal and rotated faces was developed. Two face recognition methods focusing on the aspect of pose invariance are presented and evaluated - the whole face approach and the component-based approach. The main challenge of this project is to develop a system that is able to identify faces under different viewing angles in realtime. The development of such a system will enhance the capability and robustness of current face recognition technology. The whole-face approach recognizes faces by classifying a single feature vector consisting of the gray values of the whole face image. The component-based approach first locates the facial components and extracts them. These components are normalized and combined into a single feature vector for classification. The Support Vector Machine (SVM) is used as the classifier for both approaches. Extensive tests with respect to the robustness against pose changes are performed on a database that includes faces rotated up to about 40 degrees in depth. The component-based approach clearly outperforms the whole-face approach on all tests. Although this approach isproven to be more reliable, it is still too slow for real-time applications. That is the reason why a real-time face recognition system using the whole-face approach is implemented to recognize people in color video sequences.

Evaluation of sets of oriented and non-oriented receptive fields as local descriptors

Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. We propose a performance criterion for a local descriptor based on the tradeoff between selectivity and invariance. In this paper, we evaluate several local descriptors with respect to selectivity and invariance. The descriptors that we evaluated are Gaussian derivatives up to the third order, gray image patches, and Laplacian-based descriptors with either three scales or one scale filters. We compare selectivity and invariance to several affine changes such as rotation, scale, brightness, and viewpoint. Comparisons have been made keeping the dimensionality of the descriptors roughly constant. The overall results indicate a good performance by the descriptor based on a set of oriented Gaussian filters. It is interesting that oriented receptive fields similar to the Gaussian derivatives as well as receptive fields similar to the Laplacian are found in primate visual cortex.

Correction of shading effects in vision-based UUV localization

This paper describes the improvements achieved in our mosaicking system to assist unmanned underwater vehicle navigation. A major advance has been attained in the processing of images of the ocean floor when light absorption effects are evident. Due to the absorption of natural light, underwater vehicles often require artificial light sources attached to them to provide the adequate illumination for processing underwater images. Unfortunately, these flashlights tend to illuminate the scene in a nonuniform fashion. In this paper a technique to correct non-uniform lighting is proposed. The acquired frames are compensated through a point-by-point division of the image by an estimation of the illumination field. Then, the gray-levels of the obtained image remapped to enhance image contrast. Experiments with real images are presented

Detection of matchings in a sequence of underwater images through texture analysis

This paper presents an approach to ameliorate the reliability of the correspondence points relating two consecutive images of a sequence. The images are especially difficult to handle, since they have been acquired by a camera looking at the sea floor while carried by an underwater robot. Underwater images are usually difficult to process due to light absorption, changing image radiance and lack of well-defined features. A new approach based on gray-level region matching and selective texture analysis significantly improves the matching reliability

Parámetros cuantitativos de la resonancia magnética cerebral en esclerosis múltiple y su correlación con la discapacidad

A pesar del amplio uso de la resonancia magnética en la esclerosis múltiple no se ha logrado una adecuada correlación clínico-imagenológica en esta enfermedad. Objetivo: Determinar la correlación del volumen normalizado de sustancia gris y del volumen de lesiones hipointensas en T1 obtenidos a partir de la resonancia magnética cerebral con la escala de discapacidad extendida en pacientes con diagnóstico de esclerosis múltiple. Materiales y métodos: Estudio retrospectivo en pacientes con diagnóstico de esclerosis múltiple de la Fundación Cardioinfantil. Se obtuvieron los resultados de la escala de discapacidad expandida así como análisis cuantitativo de las imágenes correspondientes de resonancia magnética por medio de la herramienta SIENA. Se cuantificaron el volumen del parénquima cerebral, sustancia gris, sustancia blanca y volumen de lesiones hipointensas en T1. Posteriormente, se relacionaron estos resultados con la escala de discapacidad extendida de Kurtzke previamente obtenida. Para el análisis estadístico se emplearon el test correlación de Spearman y t de Student y Hotelling. Resultados: Se incluyeron 58 pacientes, encontrándose correlaciones estadísticamente significativas entre la escala de discapacidad extendida y volumen de parénquima cerebral, volumen de sustancia gris y volumen de lesiones hipointensas en T1; de 0.384, 0.386 y 0.39. No se encontró una relación entre el volumen de sustancia blanca y la escala de discapacidad. Conclusiones: Existe una correlación clínico-imagenológica moderada en la esclerosis múltiple. La cuantificación de los parámetros propuestos en este estudio podría ser utilizada como herramienta en el seguimiento de la enfermedad y monitorización de nuevos tratamientos.

Eficacia de la n-acetilcisteína en nefropatía inducida por contraste en pacientes con alteración renal previa: meta-análisis. (METACIAKI)

INTRODUCCIÓN: Se define lesión renal aguda inducida por contraste (CIAKI), al deterioro de la función renal en las 48 horas posteriores a la administración de radiofármacos. Para prevenir este evento se han estudiado diversas intervenciones clínicas, como la administración de N-Acetilcisteina (NAC), previa al procedimiento diagnóstico. Meta-análisis anteriores comparan diferentes intervenciones clínicas para prevenir CIAKI sin resultados concluyentes. El presente meta-análisis analiza la evidencia de la eficacia la administración de NAC previa al procedimiento diagnóstico para prevenir CIAKI en pacientes con nefropatía previa. METODOLOGÍA: Se analizaron por 3 revisores independientes estudios ECCA, en población con nefropatía, en inglés, español, portugués, italiano, alemán y francés tanto publicados como de literatura gris, en donde se comparara NAC versus hidratación o placebo. RESULTADOS: Los estudios encontrados fueron publicados entre el año 2000 y 2010. Se analizaron 37 reportes con 6.022 pacientes. La correlación intraclase para tres observadores fue kappa r=0.97 [IC95% 0.93-0.99]). Los pacientes con nefropatía a quienes se les administró NAC previo al procedimiento tuvieron un 34% menos de probabilidad de hacer falla renal aguda, con OR ajustado por sesgo de publicación de 0.66 [IC95% 0.50-0.88] con un p de 0.002. Al realizar análisis de sensibilidad por la escala de Jadad, se encuentra que los resultados en los estudios con baja calidad no son significativos (p=0.202). CONCLUSION: Los resultados soportan la asociación entre el tratamiento preventivo con N-Acetilcisteina y una menor frecuencia de lesión renal aguda inducida por medio de contraste en pacientes nefrópatas.

Aprepitant para la prevención de la nausea y el vomito postoperatorio, una revisión sistemática de la literatura.

Objetivo: Comparar la efectividad y seguridad del uso de aprepitant contra placebo y otros antieméticos para la prevención de nausea y vomito posoperatorio (NVPO). Métodos: Se realizo una revisión sistemática incluyendo experimentos clínicos controlados realizados en pacientes adultos sometidos a cirugías bajo anestesia general. Se hizo una búsqueda en bases de datos (PUBMED, EMBASE, LILACS) y con los estudios pertinentes, se complementó con una nueva búsqueda en bola de nieve y en fuentes de literatura gris Resultados: Se incluyeron seis estudios, dos considerados de bajo riesgo, uno de riesgo incierto y tres de alto riesgo, comparando aprepitant contra placebo y contra otros antieméticos, encontrando el aprepitant tiene diferencia significativa con respecto a placebo como profilaxis de nausea y vomito postoperatorio (NVPO) con (RR 0,48; IC 95%, 0,37 a 0,64 con una p < 0.001), no hay diferencia significativa comparando su efectividad contra ondansetron (RR: 0.90, IC 95%, 0.75 a 1.07 con una p = 0.24). Al igual no se encontró diferencias significativas de estancia en unidad de cuidado post anestésicos (UCPA) (RR: 6.5, IC 95%: -21.54 a 8.54 con una p = 0.40) ni en efectos adversos cuando se compara contra otros antieméticos de (RR: 0.95 con IC 95%: 0.86 a 1.04con una p de 0.67) Conclusiones: El aprepitant es una opción atractiva para su uso como profilaxis de NVPO comprobada eficacia contra placebo, aunque no ha demostrado superioridad ante los otros grupos de fármacos y con un perfil de seguridad similar a los otros medicamentos antieméticos.

INFO2009 Reference List by Dynamite Platypus

INFO2009 Reference List by Jolyon Gray (jg16g08@ecs.soton.ac.uk) Rachel Gurman (rg16g08@ecs.soton.ac.uk) Dimitar Ivanov (dgi1v07@ecs.soton.ac.uk) Ona Lam (okl1g08@ecs.soton.ac.uk) David Lewis (dhl1g08@ecs.soton.ac.uk) William Sutton (wds1g08@ecs.soton.ac.uk)