The automated processing of retinal images is a widely researched area in medical image analysis. Screening systems based on the automated and accurate recognition of retinopathies enable the earlier diagnosis of diseases like diabetic retinopathy, hypertension and their complications. The segmentation of the vascular system is a crucial task in the field: on the one hand, the accurate extraction of the vessel pixels aids the detection of other anatomical parts (like the optic disc Hoover and Goldbaum, 2003) and lesions (like microaneurysms Sopharak et al., 2013); on the other hand, the geometrical features of the vascular system and their temporal changes are shown to be related to diseases, like the vessel tortuosity to Fabry disease Sodi et al., 2013 and the arteriolar-to-venus (A/V) ratio to hypertension (Pakter et al., 2005). In this study, a novel technique based on template matching and contour reconstruction is proposed for the segmentation of the vasculature. In the template matching step generalized Gabor function based templates are used to extract the center lines of vessels. Then, the intensity characteristics of vessel contours measured in training databases are reconstructed. The method was trained and tested on two publicly available databases, DRIVE and STARE; and reached an average accuracy of 0.9494 and 0.9610, respectively. We have also carried out cross-database tests and found that the accuracy scores are higher than that of any previous technique trained and tested on the same database.

1. The objective of this study was to evaluate the prediction potential of a computer tomography (CT) data collection protocol for determining total body composition used for analysis of tibiotarsal bone quality features. 2. The CT image acquisition was performed on 54 healthy TETRA SL genotype laying hens at 90 weeks of age as well as in the 69th week of the egg production period in vivo and their tibiotarsal bones, ex vivo. 3. Breaking strengths and ash content of the tibiotarsal bones were estimated based on the calculated mineral density of skeletal and tibiotarsal bones by means of CT with an estimation accuracy R² 0.963 and 0.975, respectively. 4. In conclusion, the current investigation demonstrated that the acquisition protocol of CT for total-body composition analysis has a good potential for measuring the mineral status and breaking strength of the reference bone in laying hen.

In this paper, a novel dissimilarity measure called Matching by Monotonic Tone Mapping (MMTM) is proposed. The MMTM technique allows matching under non-linear monotonic tone mappings and can be computed efficiently when the tone mappings are approximated by piecewise constant or piecewise linear functions. The proposed method is evaluated in various template matching scenarios involving simulated and real images, and compared to other measures developed to be invariant to monotonic intensity transformations. The results show that the MMTM technique is a highly competitive alternative of conventional measures in problems where possible tone mappings are close to monotonic.