机构

• 自动化研究所 [4]
• 计算技术研究所 [3]
• 长春光学精密机械与物... [1]
• 沈阳自动化研究所 [1]
• 西安光学精密机械研究... [1]

采集方式

• OAI收割 [10]

内容类型

• 期刊论文 [9]
• 会议论文 [1]

发表日期

• 2024 [2]
• 2023 [1]
• 2021 [3]
• 2017 [1]
• 2016 [1]
• 2013 [1]
• 更多

学科主题

筛选

浏览/检索结果: 共10条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Lung Nodule Segmentation and Uncertain Region Prediction With an Uncertainty-Aware Attention Mechanism 期刊论文  OAI收割 IEEE TRANSACTIONS ON MEDICAL IMAGING, 2024, 卷号: 43, 期号: 4, 页码: 1284-1295 作者:  Yang, Han;  Wang, Qiuli;  Zhang, Yue;  An, Zhulin;  Liu, Chen   |  收藏  |  浏览/下载：11/0  |  提交时间：2024/12/06 Lung nodules segmentation  uncertainty  multiple annotations  computed tomography   Multilevel Attention Unet Segmentation Algorithm for Lung Cancer Based on CT Images 期刊论文  OAI收割 CMC-COMPUTERS MATERIALS & CONTINUA, 2024, 卷号: 78, 期号: 2, 页码: 1569-1589 作者:  Wang, Huan;  Qiu, Shi;  Zhang, Benyue;  Xiao, Lixuan   |  收藏  |  浏览/下载：9/0  |  提交时间：2024/07/25 Lung cancer  computed tomography  computer-aided diagnosis  Unet  segmentation   Accurate Lung Nodule Segmentation With Detailed Representation Transfer and Soft Mask Supervision 期刊论文  OAI收割 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 13 作者:  Wang, Changwei;  Xu, Rongtao;  Xu, Shibiao;  Meng, Weiliang;  Xiao, Jun   |  收藏  |  浏览/下载：13/0  |  提交时间：2023/12/21 Detailed representation transfer  lung nodules segmentation  medical images segmentation  soft mask   SCOAT-Net: A novel network for segmenting COVID-19 lung opacification from CT images 期刊论文  OAI收割 PATTERN RECOGNITION, 2021, 卷号: 119, 页码: 12 作者:  Zhao, Shixuan;  Li, Zhidan;  Chen, Yang;  Zhao, Wei;  Xie, Xingzhi   |  收藏  |  浏览/下载：44/0  |  提交时间：2021/12/01 COVID-19  Convolutional neural network  Segmentation  Lung opacification  Attention mechanism   Toward data-efficient learning: A benchmark for COVID-19 CT lung and infection segmentation 期刊论文  OAI收割 MEDICAL PHYSICS, 2021, 页码: 14 作者:  Ma, Jun;  Wang, Yixin;  An, Xingle;  Ge, Cheng;  Yu, Ziqi   |  收藏  |  浏览/下载：31/0  |  提交时间：2021/12/01 COVID‐  19 CT  domain generalization  few‐  shot learning  knowledge transfer  lung and infection segmentation   Automatic Lung Segmentation Algorithm on Chest X-ray Images Based on Fusion Variational Auto-Encoder and Three-Terminal Attention Mechanism 期刊论文  OAI收割 SYMMETRY-BASEL, 2021, 卷号: 13, 期号: 5, 页码: 1-15 作者:  Cao FD(曹飞道);  Zhao HC(赵怀慈)   |  收藏  |  浏览/下载：39/0  |  提交时间：2021/06/12 chest X-ray images  U-Net  variational auto-encoder  three-terminal attention mechanism  lung segmentation   Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation 期刊论文  OAI收割 MEDICAL IMAGE ANALYSIS, 2017, 卷号: 40, 期号: 40, 页码: 172-183 作者:  Wang, Shuo;  Zhou, Mu;  Liu, Zaiyi;  Liu, Zhenyu;  Gu, Dongsheng   |  收藏  |  浏览/下载：46/0  |  提交时间：2018/01/08 Lung Nodule Segmentation  Convolutional Neural Networks  Deep Learning  Computer-aided Diagnosis   Lung Lesion Extraction Using a Toboggan Based Growing Automatic Segmentation Approach 期刊论文  OAI收割 IEEE TRANSACTIONS ON MEDICAL IMAGING, 2016, 卷号: 35, 期号: 1, 页码: 337-353 作者:  Song, Jiangdian;  Yang, Caiyun;  Fan, Li;  Wang, Kun;  Yang, Feng 收藏  |  浏览/下载：52/0  |  提交时间：2016/03/19 Back-off mechanism  computed tomography (CT)  lung lesion segmentation  region growing  toboggan   Automated delineation of lung tumors from CT images using a single click ensemble segmentation approach 期刊论文  OAI收割 PATTERN RECOGNITION, 2013, 卷号: 46, 期号: 3, 页码: 692-702 作者:  Gu, Yuhua;  Kumar, Virendra;  Hall, Lawrence O.;  Goldgof, Dmitry B.;  Li, Ching-Yen 收藏  |  浏览/下载：28/0  |  提交时间：2015/08/12 Image features  Delineation  Lung tumor  Lesion  CT  Region growing  Ensemble segmentation   MGRG-morphological gradient based 3D region growing algorithm for airway tree segmentation in image guided intervention therapy (EI CONFERENCE) 会议论文  OAI收割 2nd International Symposium on Bioelectronics and Bioinformatics, ISBB 2011, November 3, 2011 - November 5, 2011, Suzhou, China 作者:  Zhang T.;  Gao X. 收藏  |  浏览/下载：43/0  |  提交时间：2013/03/25 Accurate surgical planning and guidance plays an important role in successful implementation of image guided intervention. In interventional lung cancer diagnosis and treatments  precise segmentation of airway trees from lung CT images provides crucial visualization for preoperative planning and intraoperative guidance to avoid major trachea injury. While 3D region growing can segment main the parts of an airway tree (trachea  left and right main bronchus  as well as bronchi)  the method fails at bronchiole segmentation and is not robust. Mathematical morphology is an anatomical detective. In this paper  we propose a morphological gradient based region growing (MGRG) algorithm to overcome the intensity inhomogeneity  and improve the robustness of 3D region growing on extraction of bronchioles. The MGRG algorithm is validated using lung CT images  and results show that it is able to segment bronchioles  and outperforms the traditional region growing method on airway tree segmentation. 2011 IEEE.