Simulated movies of fluorescently stained bacteria

Wiesmann V, Bergler M, Münzenmayer C, Wittenberg T. Simulated movies of fluorescently stained bacteria. Fraunhofer Institute for Integrated Circuits, Erlangen, Germany; 2017.Simulated biomovies of fluorescent cells were created by employing cell simulation based on shape, texture, growth and motion information. They are depicted in fluorescent channels where noise and other artifacts were additionally modeled. While the original cell simulation software (Wiesmann et al. 2013) has been extended for biomovie simulation, the step for bacterial growth simulation is similar to image simulation. First, the cell shape is calculated. Second, the cell position on the image grid is calculated. Third, the cell texture is added. Fourth and last, imaging artifacts and noise are added to the final image

Characterizing mammographic images by using generic texture features

Introduction Although mammographic density is an established risk factor for breast cancer, its use is limited in clinical practice because of a lack of automated and standardized measurement methods. The aims of this study were to evaluate a variety of automated texture features in mammograms as risk factors for breast cancer and to compare them with the percentage mammographic density (PMD) by using a case-control study design. Methods A case-control study including 864 cases and 418 controls was analyzed automatically. Four hundred seventy features were explored as possible risk factors for breast cancer. These included statistical features, moment-based features, spectral-energy features, and form-based features. An elaborate variable selection process using logistic regression analyses was performed to identify those features that were associated with case-control status. In addition, PMD was assessed and included in the regression model. Results Of the 470 image-analysis features explored, 46 remained in the final logistic regression model. An area under the curve of 0.79, with an odds ratio per standard deviation change of 2.88 (95% CI, 2.28 to 3.65), was obtained with validation data. Adding the PMD did not improve the final model. Conclusions Using texture features to predict the risk of breast cancer appears feasible. PMD did not show any additional value in this study. With regard to the features assessed, most of the analysis tools appeared to reflect mammographic density, although some features did not correlate with PMD. It remains to be investigated in larger case-control studies whether these features can contribute to increased prediction accuracy

A Knowledge-based System for the Computer Assisted Diagnosis of Endoscopic Images

Abstract. Due to the actual demographic development the use of Computer-Assisted Diagnosis (CAD) systems becomes a more important part of clinical workflows and clinical decision making. Because changes on the mucosa of the esophagus can indicate the first stage of cancerous developments, there is a large interest to detect and correctly diagnose any such lesion. We present a knowledge-based system which is able to support a physician with the interpretation and diagnosis of endoscopic images of the esophagus. Our system is designed to support the physician directly during the examination of the patient, thus prodving diagnostic assistence at the point of care (POC). Based on an interactively marked region in an endoscopic image of interest, the system provides a diagnostic suggestion, based on an annotated reference image database. Furthermore, using relevant feedback mechanisms, the results can be enhanced interactively

System zur Visualisierung von Bilddaten

Die Erfindung bezieht sich auf ein System (5) zur Visualisierung von digitalisierten Bilddaten mit einer Bilddatenquelle (1) und einer Bilddatensenke (2). Die Bilddaten sind mindestens zwei unterschiedlichen Schichten (11, 12) zugeordnet sind, wobei für mindestens eine der Schichten (11, 12) Bilddaten in mindestens zwei unterschiedlichen Auflösungen vorliegen. Die Schichten (11, 12) zeigen eine gemeinsame Szene mit unterschiedlichen Aufnahmebedingungen. Dabei ist die Bilddatenquelle (1) derartig konfiguriert, Bilddaten zur Bilddatensenke (2) zu übermitteln, und ist die Bilddatensenke (2) derartig konfiguriert, Bilddaten von der Bilddatenquelle (1) zu empfangen und in Bezug auf eine Visualisierung zu verarbeiten. Die Bilddatenquelle (1) ist derartig konfiguriert, Bilddaten der zumindest einen Schicht (11) in den mindestens zwei unterschiedlichen Auflösungen vorrangig zu den Bilddaten von von der zumindest einen Schicht (11) unterschiedlichen Schichten (12) zu der Bilddatensenke (2) zu übermitteln. Weiterhin bezieht sich die Erfindung auf eine Vorrichtung zur Übertragung von Bilddaten und auf ein entsprechendes Verfahren

Verfahren und Vorrichtung zum Erstellen einer Mikroskopiepanoramadarstellung

Ausführungsbeispiele der vorliegenden Erfindung beziehen sich auf ein Verfahren zur Erstellung einer Mikroskopiedarstellung einer dreidimensionalen Probe mit flacher Ausdehnung in x und y Richtung. Das Verfahren umfasst folgende Schritte: a) Anordnen der flachen, dreidimensionalen Probe auf einen Positionierer; b) Aufnehmen der Probe mittels einer Bilderfassungsvorrichtung, um eine erste Mikroskopieaufnahme der Probe mit einem ersten Ausschnitt zu erhalten; c) Ändern (106) der Perspektive auf die zweidimensionale Probe in z-Richtung; d) Aufnehmen der Probe mittels der Bilderfassungsvorrichtung, um eine zweite Mikroskopieaufnahme der Probe mit einem zweiten Ausschnitt zu erhalten; e) Ermitteln einer Veränderungsinformation, die einen Rückschluss auf die Veränderung der Perspektive in z-Richtung zulässt, anhand eines Unterschieds zwischen der ersten und der zweiten Mikroskopieaufnahme; und f) Zusammenfügen der ersten und der zweiten Mikroskopieaufnahme unter Berücksichtigung der Veränderungsinformation, um die Mikroskopiepanoramadarstellung zu erhalten

T.: Illumination invariant color texture analysis based on sum- and difference-histograms

Abstract. Color texture algorithms have been under investigation for quite a few years now. However, the results of these algorithms are still under considerable influence of the illumination conditions under which the images were captured. It is strongly desireable to reduce the influence of illumination as much as possible to obtain stable and satisfying classification results even under difficult imaging conditions, as they can occur e.g. in medical applications like endoscopy. In this paper we present the analysis of a well-known texture analysis algorithm, namely the sumand difference-histogram features, with respect to illumination changes. Based on this analysis, we propose a novel set of features factoring out the illumination influence from the majority of the original features. We conclude our paper with a quantitative, experimental evaluation on artificial and real image samples.

Automatic Classification of Leukoplakia on Vocal Folds Using Color Texture Features

In this paper we present novel approaches for the computer aided diagnosis of leukoplakia on the vocal folds based on video endoscopic images of the larynx. The approaches applied for the classification of the vocal fold surface tissue are texture analysis methods, which have been enhanced to use spatial information as well as color information in one combined color texture approach. The multispectral approaches used are based on sum- and difference histograms as well as statistical geometrical features. These novel features are applied on manually segmented and preclassified regions and subregions of the vocal folds. It can be shown that the use of these combined color and texture features is dominant to approaches, which make solely use of either color or texture features.