Chronic Wound Healing Assessment System Based on Color and Texture Analysis
暂无分享,去创建一个
[1] Bengisu Tulu,et al. Smartphone-Based Wound Assessment System for Patients With Diabetes , 2015, IEEE Transactions on Biomedical Engineering.
[2] Aurobinda Routray,et al. Diagnostic and Prognostic Utility of Non-Invasive Multimodal Imaging in Chronic Wound Monitoring: a Systematic Review , 2017, Journal of Medical Systems.
[3] Sylvio Barbon Junior,et al. Color energy as a seed descriptor for image segmentation with region growing algorithms on skin wound images , 2014, 2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom).
[4] Neil D. Reeves,et al. Fully convolutional networks for diabetic foot ulcer segmentation , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).
[5] Ayman El-Baz,et al. Classification of pressure ulcer tissues with 3D convolutional neural network , 2018, Medical & Biological Engineering & Computing.
[6] Saurabh Maheshwari,et al. Contrast limited adaptive histogram equalization based enhancement for real time video system , 2014, 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI).
[7] Sébastien Chabrier,et al. Chromatic Indices in the Normalized rgb Color Space , 2017, 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA).
[8] Christos P. Loizou,et al. Evaluation of wound healing process based on texture analysis , 2012, 2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE).
[9] Bo Song,et al. Automated wound identification system based on image segmentation and Artificial Neural Networks , 2012, 2012 IEEE International Conference on Bioinformatics and Biomedicine.
[10] T. K. Hunt,et al. Human skin wounds: A major and snowballing threat to public health and the economy , 2009, Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society.
[11] Nicolas Gillis,et al. The Why and How of Nonnegative Matrix Factorization , 2014, ArXiv.
[12] Chandan Chakraborty,et al. Automated Tissue Classification Framework for Reproducible Chronic Wound Assessment , 2014, BioMed research international.
[13] A. S. Malik,et al. Haemoglobin distribution in ulcers for healing assessment , 2012, 2012 4th International Conference on Intelligent and Advanced Systems (ICIAS2012).
[14] Héctor Mesa,et al. Efficient detection of wound-bed and peripheral skin with statistical colour models , 2014, Medical & Biological Engineering & Computing.
[15] Bengisu Tulu,et al. Area Determination of Diabetic Foot Ulcer Images Using a Cascaded Two-Stage SVM-Based Classification , 2017, IEEE Transactions on Biomedical Engineering.