Image smoothing can remove random statistical noise in images, but it simultaneously degrades the edge sharpness. It is hence necessary for image smoothing to achieve the best combination of the two conflicting factors, noise removal and edge preservation. For this purpose, fuzzy reasoning based on fuzzy set theory is applied to image smoothing. A proper way of smoothing for each pixel is inferred from linguistic rules of the form“If...then...”, thus differing from usual smoothing methods based on analytical rules. In the present smoothing method, three fuzzy sets, ‘small’ (S), ‘medium’ (M) and‘large’ (L), are defined by the magnitude of the gradients at the pixels; further, three smoothing filters denoted by SM1, SM2and SM3are proposed as suitable ones for pixels belonging to S, M and L respectively, How suitable SM1is for S is expressed by the fuzzy set M1. Similarly, degrees of suitability of SM2and SM3for M and L are expressed by the fuzzy sets M2and M3. The above relation between S and SM1is described using M1by the following fuzzy reasoning rule: “If ED (edge magnitude) at a pixel is S then WS (a way of smoothing) for this pixel is M1”or simply“If ED=S then WS-M1. Here, “WS=M1”is the fuzzy statement of“ (If ED=S then) SM1is suitable”. Similar rules hold between M and M2, and L and M3. From the three reasoning rules, a proper way of smoothing for each pixel is inferred if the magnitude of gradient at the pixel is given. From results for preliminary experiments, it is suggested that the present smoothing algorithm can well combine noise removal and edge preservation, and its computation time is not considerable although it uses the three smoothing filters. It is thus expected that the smoothing algorithm possesses usefulness and practicality.
A smoothing method based on fuzzy reasoning has been proposed to well combine two conflicting factors in image smoothing, noise removal and edge preservation. This smoothing algorithm is described by three linguistic rules called fuzzy reasoning rules, thus differing from usual smoothing algorithms based on analytical rules. From the three reasoning rules used, a proper way of smoothing for each pixel was inferred when the magnitude of gradient at the pixel was given. To evaluate its effectiveness, the fuzzy smoothing algorithm was applied to a simulated digital phantom image and real nuclear medicine images. Smoothing algorithm is evaluated from both its noise removal ability and edge preservation ability. How well smoothing algorithm can combine the two abilities was examined by increasing the number of smoothing iterations. Furthermore, the computation time of the fuzzy smoothing algorithm is measured to evaluate its practicality. The results are compared with those obtained by three smoothing algorithms described by analytical rules, such as a weighted averaging and a median filtering. These two have widely been used for smoothing for nuclear medicine images. All algorithms including the fuzzy smoothing one are performed on a 3×3 window. From smoothed results obtained by the smoothing algorithms, it is found that the fuzzy smoothing algorithm achieved the best combination of noise removal and edge preservation, and its computation time was reasonable. It is thus concluded that the fuzzy smoothing algorithm is useful and has a high potential for practical applications.
Selection of imaging conditions in scintigraphy was evaluated using analytic hierarchy process. First, a method of the selection was led by determining at the points of image quality and imaging time, Influence of image quality was thought to depend on changes of system resolution, count density, image size, and image density. Also influence of imaging time was thought to depend on chnages of system sensitivity and data acquisition time. Phantom study was done for paired comparison of these selection factors, and relations of sample data and the factors, that is, Rollo phantom images were taken by changing count denisty, image size, and image density. Image quality were shown by calculating the score of visual evaluation that done by comparing of a pair of images in clearer cold lesion on the scintigrams. Imaging time was shown by relative values for changes of count density. However, system resolution and system sensitivity were constant in this study. Next, using these values analytic hierarchy process was adapted for this selection of imaging conditions. We conclude that this selection of imaging conditions can be analyzed quantitatively using analytic hierarchy process and this analysis develops theoretical consideration of imaging technique.
The comparative study of the blood clearance tests of 99mTc-phytate (99mTc-P) and indocyanine green (ICG) was undertaken in liver-injured rats with carbon tetrachloride (CCl4) . The blood clearances of 99mTc-P and ICG in rats decreased with the increase in dose of CCl4 and with the time elapsed after CC14 administration, As compared with the blood clearance test of ICG, the blood clearance test of99mTc-P in rats was found to be more sensitive in detection of the hepatic dysfunction with mildly damaged stage, but to be relatively inaccurate in detection of the hepatic dysfunction with severely damaged stage induced by CCl4.
The monitoring of urinary tritium was performed on eight radiation workers who handled3H-labeled compounds more than 37 MBq, Tritium was detected from a radiation worker who disposed of a non-volatile3H-labeled compound stored for nine and a half years after the last use. The observed effective half-life was 10.8±1.9 days. It was assumed that internal contamination was caused by inadvertent inhalation of tritiated water vapor, which might be produced by a degradation of the labeled compound. Radiation workers should be properly protected by taking into account the possibility of internal contamination when they deal with originally non-volatile3H-labeled compounds stored for a long period.