A segmentation process is usually required in order to analyze an image. One of the available segmentation approaches is by detecting the edges on the image. Up to now, there are many edge detection algorithms that researchers have proposed. Thus, the purpose of this systematic literature review is to investigate the available quality assessment methods that researchers have utilized to evaluate the performance of the edge detection algorithms. Due to the vast number of available literature in this area, we limit our search to only open-access publications. A systematic search in five publisher websites (i.e., IEEExplore, IET digital library, Wiley, MDPI, and Hindawi) and Scopus database was carried out to gather resources that are related to the edge detection algorithms. Seventy-three publications that are about developing or comparing edge detection algorithms have been chosen. From these publication samples, we have identified 17 quality assessment methods used by researchers. Among the popular quality assessment methods are visual inspection, processing time, confusion-matrix based measures, mean square error (MSE)-based measures, and figure of merit (FOM). This survey also indicates that although most of the researchers only use a small number of test images (i.e., less than 10 test images), there are available datasets with a larger number of images for digital image segmentation that researchers can utilize.INDEX TERMS Digital image processing, edge detection algorithm, image segmentation, assessment, validation, quality measures, reviews.
Purpose: To investigate the effect of using higher x‐ray tube voltage (kVp), than those recommended by manufacturers, on patient dose and image quality during digital radiography (DR) examination of the Lumber Spine. Methods: Reference images of an RSD (Radiology Support Devices, Long Beach, CA, USA) anthropomorphic lumber spine phantom were obtained using 3 different DR systems using exposure factors, kVp and tube‐current time product (mAs), recommended by the manufacturer of each system. Test images were obtained, on each system, using kVp values which were 15% and 30% higher than those recommended by the respective manufacturers, while reducing the mAs to 50% and 25% respectively of the reference exposure. The images were evaluated subjectively by 3 experienced Radiologist using the image quality criteria recommended by the Commission of the European Communities (CEC) for LS examination, on a 5‐point scale. For each image, the entrance surface exposure, including backscatter, to the phantom was measured using the Victoreen Model 8000 NERO TM mAx system and the entrance surface dose and effective dose were calculated. Any statistically significant differences between the average scores for the images were tested using Kruskal‐Wallis test at p=0.05. Results: The average score from the 3 Radiologists were above the clinically acceptable levels for all of the images. Within each system, the average scores for the images obtained with different exposure factors did not show any statistically significant differences. The entrance surface doses to the phantom and the calculated effective doses decreased by approximately 30% for a kVp increase of 15% and approximately by 50% for kVp increase of 30% in all 3 systems. Conclusions: Dose reduction up to 50% can be achieved without affecting the diagnostic quality of all images in the 3 systems by using kVp and mAs values other than those recommended by the DR systemˈs manufacturer.
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