Automatic X-ray landmark detection and shape segmentation via data-driven joint estimation of image displacements

In this paper, we propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. To detect landmarks, we estimate the displacements from some randomly sampled image patches to the (unknown) landmark positions, and then we integrate these predictions via a voting scheme. Our key contribution is a new algorithm for estimating these displacements. Different from other methods where each image patch independently predicts its displacement, we jointly estimate the displacements from all patches together in a data driven way, by considering not only the training data but also geometric constraints on the test image. The displacements estimation is formulated as a convex optimization problem that can be solved efficiently. Finally, we use the sparse shape composition model as the a priori information to regularize the landmark positions and thus generate the segmented shape contour. We validate our method on X-ray image datasets of three different anatomical structures: complete femur, proximal femur and pelvis. Experiments show that our method is accurate and robust in landmark detection, and, combined with the shape model, gives a better or comparable performance in shape segmentation compared to state-of-the art methods. Finally, a preliminary study using CT data shows the extensibility of our method to 3D data.

Value Priorities and Content of Religiosity - New Research Perspectives

In this study the relationship of religiosity and value priorities is differentiated, based on a multidimensional measurement of different contents of religiosity. The structure of values is conceptualized using Schwartz’ (1992) two orthogonal dimensions of Self-transcendence vs. Self-enhancement and Openness to change vs. Conservation. The relations between these two dimensions and eight religious contents, ranging from open-minded to more close-minded forms of religiosity, were tested in a sample of church attenders (N = 685), gathered in Germany. The results show, that depending on the content of religiosity, different values are preferred (self-direction, universalism, benevolence, tradition and security values). The results indicate the importance of the content of religiosity for predicting value-loaded behaviors.

Synergistic action of image-guided radiotherapy and androgen deprivation therapy.

The combined use of androgen deprivation therapy (ADT) and image-guided radiotherapy (IGRT) can improve overall survival in aggressive, localized prostate cancer. However, owing to the adverse effects of prolonged ADT, it is imperative to identify the patients who would benefit from this combined-modality therapy relative to the use of IGRT alone. Opportunities exist for more personalized approaches in treating aggressive, locally advanced prostate cancer. Biomarkers--such as disseminated tumour cells, circulating tumour cells, genomic signatures and molecular imaging techniques--could identify the patients who are at greatest risk for systemic metastases and who would benefit from the addition of systemic ADT. By contrast, when biomarkers of systemic disease are not present, treatment could proceed using local IGRT alone. The choice of drug, treatment duration and timing of ADT relative to IGRT could be predicated on these personalized approaches to prostate cancer medicine. These novel treatment intensification and reduction strategies could result in improved prostate-cancer-specific survival and overall survival, without incurring the added expense of metabolic syndrome and other adverse effects of ADT in all patients.