Right ventricle extraction by low level and model-based algorithm

In this paper we present an algorithm as the combination of a low level morphological operation and model based Global Circular Shortest Path scheme to explore the segmentation of the Right Ventricle. Traditional morphological operations were employed to obtain the region of interest, and adjust it to generate a mask. The image cropped by the mask is then partitioned into a few overlapping regions. Global Circular Shortest Path algorithm is then applied to extract the contour from each partition. The final step is to re-assemble the partitions to create the whole contour. The technique is deemed quite reliable and robust, as this is illustrated by a very good agreement between the extracted contour and the expert manual drawing output.

Identifying and discriminating among lucerne cultivars using plant morphological characters

The use of morphological data obtained from field (plot test) and glasshouse trials to identify and discriminate among four Iranian and two New Zealand lucerne (Medicago sativa L.) cultivars was investigated, following guidelines established by the International Union for the Protection of New Varieties of Plants (UPOV) for cultivar registration and the Organisation for Economic Co-operation and Development (OECD) for seed certification. Data were collected for terminal leaflet length, width and ratio, angle of stem growth, date of first flowering, stem height at first flowering, flower colour, cutting recovery height, and disease scores. None of these characters were sufficient to identify or discriminate among the six cultivars. The results indicate a need to find cost-effective and efficient laboratory techniques to enhance the assessment of distinctness of lucerne cultivars (UPOV) and for determining cultivar purity for lucerne seed certification (OECD).