Published on in Vol 10, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28880, first published .
Using a Convolutional Neural Network and Convolutional Long Short-term Memory to Automatically Detect Aneurysms on 2D Digital Subtraction Angiography Images: Framework Development and Validation

Using a Convolutional Neural Network and Convolutional Long Short-term Memory to Automatically Detect Aneurysms on 2D Digital Subtraction Angiography Images: Framework Development and Validation

Using a Convolutional Neural Network and Convolutional Long Short-term Memory to Automatically Detect Aneurysms on 2D Digital Subtraction Angiography Images: Framework Development and Validation

JunHua Liao   1, 2 * , BSc ;   LunXin Liu   1 * , MD ;   HaiHan Duan   3 , MSc ;   YunZhi Huang   4 , PhD ;   LiangXue Zhou   1 , MD ;   LiangYin Chen   2 , PhD ;   ChaoHua Wang   1 , MD

1 Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China

2 College of Computer Science, Sichuan University, Chengdu, China

3 School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China

4 School of Automation, Nanjing University of Information Science and Technology, Nanjing, China

*these authors contributed equally

Corresponding Author:

  • ChaoHua Wang, MD
  • Department of Neurosurgery
  • West China Hospital
  • Sichuan University
  • No. 37 Guoxue Lane, Wuhou District
  • Chengdu, 610041
  • China
  • Phone: 86 18628169123
  • Email: wangchaohuaHX@163.com