Precise Segmentation and Classification of Epithelial Rete-Pegs Signature in Assessing Lower Limb Wound Healing Progression-Reference-Cited by-同舟云学术

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Precise Segmentation and Classification of Epithelial Rete-Pegs Signature in Assessing Lower Limb Wound Healing Progression

Published:2018-07-26 Issue:1 Volume:39 Page:151-162
ISSN:1609-0985
Container-title:Journal of Medical and Biological Engineering
language:en
Short-container-title:J. Med. Biol. Eng.

Author:

Dey Susmita,Ray Asmita,Maiti Narayan Chandra,Banerjee Provas,Chatterjee Jyotirmoy,Maity Santi Prasad,Roychowdhury Amit,Barui Ananya

Funder

TEQIP 2

Publisher

Springer Science and Business Media LLC

Subject

Biomedical Engineering,General Medicine

Link

http://link.springer.com/article/10.1007/s40846-018-0442-6/fulltext.html

Reference52 articles.

1. Nunan, R., Harding, K. G., & Martin, P. (2014). Clinical challenges of chronic wounds: Searching for an optimal animal model to recapitulate their complexity. Disease Models & Mechanisms, 7(11), 1205–1213. https://doi.org/10.1242/dmm.016782 .

2. Fauzi, M. F. A., Khansa, I., Catignani, K., et al. (2015). Computerized segmentation and measurement of chronic wound images. Computers in Biology and Medicine, 60, 74–85. https://doi.org/10.1016/j.compbiomed.2015.02.015 .

3. Papazoglou, E. S., Zubkov, L., Mao, X., Neidrauer, M., Rannouy, N., & Weingarten, M. S. (2010). Image analysis of chronic wounds for determining the surface area. Wound Repair and Regeneration, 18(4), 349–358.

4. Frykberg, R. G., & Banks, J. (2015). Challenges in the treatment of chronic wounds. Advances in Wound Care, 4(9), 560–582. https://doi.org/10.1089/wound.2015.0635 .

5. Loizou, P., Kasparis, T., Mitsi, O., & Polyviou, M. (2012). Evaluation of wound healing process based on texture analysis. In Proceedings of IEEE international conference on bioinformatics and bioengineering (pp. 709–714).

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