Multi-granularity scale-aware networks for hard pixels segmentation of pulmonary nodules-Reference-Cited by-同舟云学术

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Multi-granularity scale-aware networks for hard pixels segmentation of pulmonary nodules

Published:2021-08 Issue: Volume:69 Page:102890
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Wang Kun,Zhang Xiangbo,Zhang Xiaohong,Huang Sheng,Li Jingqin,HuangFu Luwen

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing

Reference38 articles.

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2. Ct screening for lung cancer: alternative definitions of positive test result based on the national lung screening trial and international early lung cancer action program databases;Yip;Radiology,2014

3. Automatic graph cut segmentation of lesions in ct using mean shift superpixels;Ye;Int. J Biomed. Imaging,2010

4. A novel approach for lung nodules segmentation in chest ct using level sets;Farag;IEEE Trans. Image Process.,2013

5. Lung nodule segmentation and recognition using svm classifier and active contour modeling: A complete intelligent system;Keshani;Computers Biol. Med.,2013

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1. Lung Cancer Detection Systems Applied to Medical Images: A State-of-the-Art Survey;Archives of Computational Methods in Engineering;2024-05-22

2. A Dual-Branch Framework With Prior Knowledge for Precise Segmentation of Lung Nodules in Challenging CT Scans;IEEE Journal of Biomedical and Health Informatics;2024-03

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

4. Factors influencing the outcome of volumetry tools for pulmonary nodule analysis: a systematic review and attempted meta-analysis;Insights into Imaging;2023-09-23

5. SAtUNet: Series atrous convolution enhanced U‐Net for lung nodule segmentation;International Journal of Imaging Systems and Technology;2023-09-15

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