No abstract

An accurate detection of the radiation field is crucial to 3D conformal radiotherapy (3D‐CRT). Automated techniques to detect the field edges on double exposure portal images have previously focused on thresholding techniques. In this paper, we present a new approach based on a curve propagation technique (the Fast Marching method) which proves to be more effective at detecting the radiation field than its thresholding counterpart. The comparison of both techniques in terms of computational speed and effectiveness of the detection is presented using complex images with non‐homogeneous intensity levels inside the radiation field, and gradual variations in intensity level at the field boundaries. Results show that our Fast Marching method is easier to automate, and converges faster to the boundaries of the segmented radiation field. The computation time of the Fast Marching technique is five times faster in typical portal images.PACS numbers: 87.53.Oq, 87.57.Nk, 87.57.‐s.

Hash joins combine massive relations in data warehouses, decision support systems, and scientific data stores. Faster hash join performance significantly improves query throughput, response time, and overall system performance. In this work, we demonstrate how using join cardinality improves hash join performance. The key contribution is the development of an algorithm to determine join cardinality in an arbitrary query plan. We implemented early hash join and the join cardinality algorithm in PostgreSQL. Experimental results demonstrate that early hash join has an immediate response time that is an order of magnitude faster than the existing hybrid hash join implementation. One-to-one joins execute up to 50% faster and perform significantly fewer I/Os, and one-to-many joins have similar or better performance over all memory sizes.