Automatic Processing and Analysis of the Quality Healing of Derma Injury

Automation of analyzing the biological data can increase the quality of analyses and decrease spending time. Analyze of the microscope’s bitmaps is usual task in biology. To illustrate the proposed method we used analyzing collagen in dermis snapshots. Methodic to automatic analyses of microscope snapshots is presented. Object of analysis can be determine by color vector. Then the snapshot can be binarized and meshed. For every element we can restore distribution of the mean intercept length. Orientation of the objects can be calculated using approximation of the mean intercept length. Equation to estimate the quality of collagen recovery was presented. We used the method on samples of three types: no ficin group (N), ficin group (F), immobilized ficin (Fi). We tested 10 bitmaps for every group and we got results for all bitmaps according described technique. Quality of collagen recovery values was: for N group – 48% ± 8%, for F group 78 ± 7%, for Fi group 68 ± 9%. It can be concluded that ficin positively influence on dermas recovery. Received results are consistent with published results.