文章基本信息

标题：A Novel Deep Learning Network and Its Application for Pulmonary Nodule Segmentation
本地全文：下载
作者：Dechuan Lu ; Junfeng Chu ; Rongrong Zhao 等
期刊名称：Computational Intelligence and Neuroscience
印刷版ISSN：1687-5265
电子版ISSN：1687-5273
出版年度：2022
卷号：2022
DOI：10.1155/2022/7124902
语种：English
出版社：Hindawi Publishing Corporation
摘要：Pulmonary nodules are the early manifestation of lung cancer, which appear as circular shadow of no more than 3 cm on the computed tomography (CT) image. Accurate segmentation of the contours of pulmonary nodules can help doctors improve the efficiency of diagnosis. Deep learning has achieved great success in computer vision. In this study, we propose a novel network for pulmonary nodule segmentation from CT images based on U-NET. The proposed network has two merits: one is that it introduces dense connection to transfer and utilize features. Additionally, the problem of gradient disappearance can be avoided. The second is that it introduces a new loss function which is tolerance on the pixels near the borders of the nodule. Experimental results show that the proposed network at least achieves 1% improvement compared with other state-of-art networks in terms of different criteria.