Burns : journal of the International Society for Burn Injuries
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Burns are a serious health problem leading to several thousand deaths annually, and despite the growth of science and technology, automated burns diagnosis still remains a major challenge. Researchers have been exploring visual images-based automated approaches for burn diagnosis. Noting that the impact of a burn on a particular body part can be related to the skin thickness factor, we propose a deep convolutional neural network based body part-specific burns severity assessment model (BPBSAM). ⋯ The main contributions of this work along with burn images labelled datasets creation is that the proposed customized body part-specific burn severity assessment model can significantly improve the performance in spite of having small burn images dataset. This highly innovative customized body part-specific approach could also be used to deal with the burn region segmentation problem. Moreover, fine tuning on pre-trained non-burn body part images network has proven to be robust and reliable.
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Laser has found increasingly wider applications in the medical filed, but laser is likely to cause damage to patients' skin. In this experiment, we were surprised to find that glyceryl monooleate (GMO)-based cubic liquid crystal had excellent healing effect on the skin of guinea pigs damaged by laser. ⋯ GMO-based cubic liquid crystals had an obvious effect in the treatment of slight and moderate laser damage. This finding may provide a effective medical treatment protocols for laser skin damage.