Development of new image evaluation software and its applicability in the in vivo prediction of egg yolk content in hen’s eggs depending on some CT aquisition parameters
The present study was designed to determine the in vivo predictability of egg yolk content in hens’ eggs by means of computer tomography (CT), depending on some aquisition parameters. The experiment was carried out with altogether 120 eggs, which were originated from a 36 week old TETRA-H parent stock. During the CT measurements eggs were positioned in egg holders (10 eggs), thus two eggs were scanned simultaneously. The scanning parameters were: 80−110−130 kV and 40−80−120 mAs in 9 possible combinations, spiral mode, pitch 1, field of view 110 mm. In all cases eggs were scanned using overlapping 3 mm slice thickness on a Siemens Somatom Emotion 6 multislice CT scanner. On the images obtained the volume of the yolk was determined using a self-developed egg-separation and segmentation software. After the CT measurements eggs were broken and their yolk weight was measured. Pearson correlations were calculated between the CT predicted yolk volume and the measured yolk weight. It was established that the higher tube voltage settings of 110 and 130 kV resulted in higher correlation (r=0.78−0.79) between these two examined traits than the lower voltage setting of 80 kV (0.75−0.76). The X-ray dose (mAs) had no significant effect on the correlation coefficients. Based on these results it was concluded that further development of this method is needed in order to obtain the similar accuracy of prediction in the case of egg components as it was already reached in the case of body composition in different animal species. For this purpose the egg-segmentation software has to be tested with modified algorythms. Further optimization of the measurement parameters might need to be considered as well.