The Development of a Skin Image Analysis Tool by Using Machine Learning Algorithms

We present our latest research work on the development of a skin image analysis tool by using machine-learning algorithms. Skin imaging is very import in skin research. Over the years, we have used and developed different types of skin imaging techniques. As the number of skin images and the type of skin images increase, there is a need of a dedicated skin image analysis tool. In this paper, we report the development of such software tool by using the latest MATLAB App Designer. It is simple, user friendly and yet powerful. We intend to make it available on GitHub, so that others can benefit from the software. This is an ongoing project; we are reporting here what we have achieved so far, and more functions will be added to the software in the future.

[1]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[2]  Fabrizio Smeraldi,et al.  Personal identification based on skin texture features from the forearm and multi‐modal imaging , 2017, Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging.

[3]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[4]  S. Menzies,et al.  Dermoscopy compared with naked eye examination for the diagnosis of primary melanoma: a meta‐analysis of studies performed in a clinical setting , 2008, The British journal of dermatology.

[5]  Wei Pan,et al.  In-Vivo Skin Capacitive Image Classification Using AlexNet Convolution Neural Network , 2018, 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC).

[6]  Perry Xiao,et al.  Skin Capacitive Imaging Analysis Using Deep Learning GoogLeNet , 2020, SAI.

[7]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[8]  Xu Zhang,et al.  Micro‐relief analysis with skin capacitive imaging , 2018, Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging.

[9]  Perry Xiao,et al.  In vivo skin capacitive imaging analysis by using grey level co-occurrence matrix (GLCM). , 2014, International journal of pharmaceutics.

[10]  X Ou,et al.  Skin image retrieval using Gabor wavelet texture feature , 2016, International journal of cosmetic science.

[11]  H P Soyer,et al.  Dermoscopy of pigmented skin lesions--a valuable tool for early diagnosis of melanoma. , 2001, The Lancet. Oncology.

[12]  Dumitru Erhan,et al.  Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).