@inproceedings{f1caecaa04a54d70a9966b035f16454a,
title = "Two-Way Perceived Color Difference Saliency Algorithm for Image Segmentation of Port Wine Stains",
abstract = "The image segmentation of port wine stains (PWS) lesions is of great significance to assess PDT treatment outcomes. However, it mainly depends on the manual division of doctors at present, which is time-consuming and laborious. Therefore, it is urgent and necessary to explore an efficient and accurate automatic extraction method for PWS lesion images. A two-way perceived color difference saliency algorithm (TPCS) for PWS lesion extraction is proposed to improve the efficiency and accuracy, and is compared with other image segmentation algorithms. The proposed algorithm shows the best performance with 88.91% accuracy and 96.36% sensitivity over 34 test images of PWS lesions.",
keywords = "Image segmentation, Port wine stains, Saliency algorithm",
author = "Wenrui Kang and Xu Wang and Jixia Zhang and Xiaoming Hu and Qin Li",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Singapore Pte Ltd.; 1st BenchCouncil International Federated Intelligent Computing and Block Chain Conferences, FICC 2020 ; Conference date: 30-10-2020 Through 03-11-2020",
year = "2021",
doi = "10.1007/978-981-16-1160-5_5",
language = "English",
isbn = "9789811611599",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "50--60",
editor = "Wanling Gao and Kai Hwang and Changyun Wang and Weiping Li and Zhigang Qiu and Lei Wang and Aoying Zhou and Weining Qian and Cheqing Jin and Zhifei Zhang",
booktitle = "Intelligent Computing and Block Chain - 1st BenchCouncil International Federated Conferences, FICC 2020, Revised Selected Papers",
address = "Germany",
}