A multi-view deep convolutional neural networks for lung nodule segmentation
Shuo Wang(Kailuan General Hospital), Tian Jie(Chinese Academy of Sciences), Olivier Gevaert(Stanford Medicine), Mu Zhou(Stanford University), Zhenyu Liu(Shanxi Agricultural University), Zhenchao Tang(Shandong Institute of Automation), Di Dong(Chinese Academy of Sciences)
Cited by 118
Related Papers
Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation
|Cell|2018|2.4k
The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges
|Theranostics|2019|1k
Radiomics Analysis for Evaluation of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer
|Clinical Cancer Research|2017|562
Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation
|Medical Image Analysis|2017|489
Predicting EGFR mutation status in lung adenocarcinoma on computed tomography image using deep learning
|European Respiratory Journal|2019|441