A dual-task region-boundary aware neural network for accurate pulmonary nodule segmentation-Reference-Cited by-同舟云学术

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A dual-task region-boundary aware neural network for accurate pulmonary nodule segmentation

Published:2023-10 Issue: Volume:96 Page:103909
ISSN:1047-3203
Container-title:Journal of Visual Communication and Image Representation
language:en
Short-container-title:Journal of Visual Communication and Image Representation

Author:

Qiu Junrong,Li Bin,Liao Riqiang,Mo Hongqiang,Tian Lianfang

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Media Technology,Signal Processing

Reference39 articles.

1. Lung cancer in People’s Republic of China;Gao;J. Thorac. Oncol.,2020

2. Reduced lung-cancer mortality with low-dose computed tomographic screening;National Lung Screening Trial Research Team;N. Engl. J. Med.,2011

3. A survey of computer-aided diagnosis of lung nodules from CT scans using deep learning;Gu;Comput. Biol. Med.,2021

4. Morphological segmentation and partial volume analysis for volumetry of solid pulmonary lesions in thoracic CT scans;Kuhnigk;IEEE Trans. Med. Imaging,2006

5. An automatic random walker algorithm for segmentation of ground glass opacity pulmonary nodules;Li;J. Healthcare Eng.,2022

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Vectorial Image Representation for Image Classification;Journal of Imaging;2024-02-13

2. A comprehensive exploration of deep learning approaches for pulmonary nodule classification and segmentation in chest CT images;Neural Computing and Applications;2024-02-04

3. Pulmonary Nodule Segmentation Using Deep Learning: A Review;IEEE Access;2024

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