@inproceedings{e4c920b1fd054d2a8a9f11b709227c52,
title = "An Automatic Method of Chronic Wounds Segmentation in Multimodal Images",
abstract = "Chronic wounds are common diseases in aging society. Automatic method of images segmentation is required to effectively and objectively monitor the healing process. The segmentation method proposed in the paper employs Histograms of Oriented Gradients, Weighted Fuzzy C-Means Clustering, Edge Detection, Gradient Vector Flow and Active Contour techniques. The method gives high compliance with manual outlines performed by two experts. Mean Dice Index for 11 cases was 0.84. Obtained results indicate the possibility of automation of diagnosis and monitoring processes. An infrared image reveals the parts of the wound under the skin which are invisible for commonly used cameras and it might give valuable information for physicians in assortment of treatment.",
keywords = "Active contour, Histogram of oriented gradients, Image processing, Wound segmentation",
author = "Joanna Czajkowska and Marta Biesok and Jan Juszczyk and Agata Wijata and Bart{\l}omiej Pyci{\'n}ski and Michal Krecichwost and Ewa Pietka",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 7th International Conference on Information Technology in Biomedicine, ITIB 2019 ; Conference date: 18-06-2019 Through 20-06-2019",
year = "2019",
doi = "10.1007/978-3-030-23762-2\_22",
language = "English",
isbn = "9783030237615",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "249--257",
editor = "Ewa Pietka and Pawel Badura and Jacek Kawa and Wojciech Wieclawek",
booktitle = "Information Technology in Biomedicine, 2019",
address = "Germany",
}