Training FCNs model with lesion-size-unified dermoscopy images for lesion segmentation

doi:10.1109/ICAIBD.2018.8396187

	Training FCNs model with lesion-size-unified dermoscopy images for lesion segmentation
	Qiu, Yuming1,2 ; Qin, Xiaolin 1,3; Zhang, Ju2
	2018
会议日期	May 26, 2018 - May 28, 2018
会议地点	Chengdu, China
DOI	10.1109/ICAIBD.2018.8396187
页码	165-169
英文摘要	Dermoscopy is an important noninvasive diagnostic technique for early detection of melanoma that is the deadliest form of skin cancer. Lesion segmentation is a critical step in analyzing dermoscopy images. An obvious characteristic of the lesions in dermoscopy images is appearing in multi-size, and it becomes a serious barrier to improve the lesion segmentation while using fully convolutional neural networks (FCNs) model, which is a popular tool to carry off this challenging task. In this paper, we propose a method to unify the lesion sizes among various dermoscopy images and use the unified images to train the FCNs model. The method was tested on PH2 and ISIC2017 dataset, and the results of experiments show that using the lesion-size-unified dermoscopy images can greatly improve the segmentation performance. This work is of value on assisting artificial delineation, revealing the relations between performance and various lesion sizes, and guiding significance for preprocessing of input dermoscopy images while using FCNs model. © 2018 IEEE.
会议录	2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018
语种	英语
内容类型	会议论文
源URL	[http://119.78.100.138/handle/2HOD01W0/7972]
专题	中国科学院重庆绿色智能技术研究院
作者单位	1.Chengdu Institute of Computer Applications, Chinese Academy of Sciences, Chengdu, China; 2.Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China; 3.Academy of Intelligent Software, Guangzhou University, Guangzhou, China
推荐引用方式 GB/T 7714	Qiu, Yuming,Qin, Xiaolin,Zhang, Ju. Training FCNs model with lesion-size-unified dermoscopy images for lesion segmentation[C]. 见:. Chengdu, China. May 26, 2018 - May 28, 2018.