Polarization Characteristics And Recognition Of Burned Skin

Thermal injury of skin is common in accidental burns and large fires,and the measurement of burn depth has always been an important part of medical imaging.Rapid and accurate assessment of burn grade is a critical step in guiding the treatment of patients with thermal injury.It can determine whether the wound should be bandaged or resected,which also has a significant reference value to the body fluid resuscitation dosage.PS-OCT(polarization-sensitive optical coherence tomography)has the advantages of non-contact,non-damage,high resolution,high sensitivity,and deeper imaging depth than a microscope,and can analyze the change of the heterogeneity of skin-dermis birefringence caused by thermal injury.Because PS-OCT has such a breakthrough advantage,the medical imaging field of PS-OCT,such as ophthalmology,Dermatology,has more and more research applications.In recent years,with the rapid development of the medical imaging industry,the burden of medical experts to examine data is also increasing.The breakthrough development of deep learning can help doctors segment the damaged tissue quickly,and help doctors realize rapid and accurate treatment.Combined with deep learning,the thermal damage location of PS-OCT images can be effectively segmented by training and learning the characteristics of tissue damage.Therefore,the combination of PS-OCT and depth learning has potential application value in the non-invasive evaluation of burn depth.To detect different burn degrees of PS-OCT,a dual-detection PS-OCT imaging system has been built a dual-detection imaging algorithm is developed based on the LABVIEW video acquisition card(PCI-1433),data acquisition card(PCI-6229),and the spectrometer.We found the birefringence of mouse skin is similar to that of human skin by imaging normal human skin and normal mouse skin.The mouse back skin is scalded in hot water at55 °C,75 °C,and 90 °C for 20 seconds to simulate different human skin damage levels.By using the Jones matrix,the effects of thermal damage on the skin of mice were discussed in terms of intensity,accumulated phase retardance,accumulated optical axis,local phase retardance,and the local optical axis,respectively.It was found that thermal injury decreased the birefringence of skin,and there was a positive correlation between the two.To explain the effect of injury on the heterogeneity of birefringent tissue in collagen more directly,the pig tendon tissue rich in collagen was used as the experimental sample for further explanation.Through the method of deep learning,the damaged part of the pig tendon tissue is segmented and the depth of the injury is predicted.Finally,the damage grade of the pig tendon is judged according to the change of the birefringence of the injured part.