In this paper we present a technique for ellipse detection in digital images based on swarm intelligence algorithm and arc segment combination. The proposed method is then used as embryo quality scoring assessment during the first 24-48 hours since its morphological structure can be approximated by ellipse. The idea of the proposed algorithm are based on combining possible arcs for the ellipse shaped objects and try to find the best combinations using Particle Swarm Optimization technique to find the actual ellipse. The process involves detecting line segments in the image and then followed by arc segment extraction from lines to get potential elliptical arcs. The detection process is then guided by Particle Swarm Optimization (PSO) by utilizing the calculation of the fitness function from the arc segment that had been detected previously. The measurement results of proposed method are then compared with manual measurements. The experiment results were conducted on both synthetic data and real embryo images. Experiment results showed that the proposed method is better than several ellipse detection methods such as RHT, IRHT, and PSORHT to detect ellipses on the image. Another advantage of our proposed algorithm compared to the Hough Transform variants is that it can be used for multiple ellipse detection.

CT scan can be used to show the anatomical and pathological evaluation of Mastoid bones where an X-ray across it to create a cross-sectional image with an advanced computer. This imaging modality allows the radiologist to look at different levels of the bone ridge behind the ear. In our hospital, this procedure needs to be improved. Radiographer could make optimization by adjusting windows and developing kernel to maintain the image quality. This study aimed to obtain the optimum image of Mastoid bones, using variations of window and kernel reconstruction. The study was descriptive quantitative with an experimental approach. It resulted in eight images of two windowing levels (sinus and inner ear) and four kernel variations (smooth, medium, sharp, and ultra-sharp). Three radiologists evaluated the injury, bleedin, and soft tissue abnormalities images. The result showed that all window settings are acceptable. Kernel reconstructions have no different anatomical image information in soft tissue, Internal Auditory Canal, and External Auditory Canal. There is a difference for overall anatomical information of Mastoid bones (p value<0.05). Highest values of mean rank are obtained from sharp and ultra-sharp. Our recommendations are using the H.20s smooth kernel for soft tissue abnormalities and H.70s sharp kernel for fracture and bleeding cases.

Introduction: Quality and dose factors are very important in radiodiagnostics. To produce a constant radiographic quality, the density and contrast produced must remain constant. There is a rule that aims to produce a constant radiographic quality by adding the exposure value, namely the 10 kV rule. This study was conducted to determine the noise in the computed radiography image with the thorax organ produced by modifying the exposure factor of the 10 kV rule and whether it is still within tolerance.Methods: This quantitative research was conducted with an experimental approach. This is done by taking a series of radiographs that include three exposure factor settings, standard (60 kV, 10 mAs), increased by 10 kV (70 kV, 5 mAs) and lowered by 10 kV (50 kV, 20 mAs). Noise measurement is done by doing ROI in the background area. The exposure index and deviation index values were also recorded as quality and dose references. The data was processed and analyzed by statistical tests.Results: From the statistical test results, there is a significant relationship between kV and noise with a sig (1-tailed) of ,000. Noise on the standard exposure factor has a lower noise than the modified exposure factor with a difference of 0.2. From the quality aspect, the most optimum exposure index and deviation index indicators are in the range of 70 KV and 5 mAs.Conclusion: The results of the statistical test of the relationship of kV to noise obtained at 50 Kv and 20 mAs, 60 kV and 10 mAs gave a significance value of 0.263 and 0.435, while at 70 kV and 10 mAs with Sig. (1-tailed) of .000 which means the relationship between kV to noise is strong because the sig value is below 0.05.