Automatic heart segmentation based on 2D/3D U-plus-net(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2021年第9期
- Page:
- 1172-1178
- Research Field:
- 医学人工智能
- Publishing date:
Info
- Title:
- Automatic heart segmentation based on 2D/3D U-plus-net
- Author(s):
- SONG Yuchen1; PENG Zhao1; WU Haotian2; ZHOU Jieping3; PI Yifei4; CHEN Zhi1; PEI Xi1
- 1. Center of Radiological Medical Physics, University of Science and Technology of China, Hefei 230027, China 2. Anhui Wisdom
Technology Co., Ltd, Hefei 230000, China 3. Department of Radiation Oncology, the First Affiliated Hospital of University of Science
and Technology of China, Hefei 230001, China 4. Department of Radiation Oncology, the First Affiliated Hospital of Zhengzhou
University, Zhengzhou 450052, China
- Keywords:
- heartAlexNet 2D U-plus-net 3D U-plus-net automatic segmentation
- PACS:
- R318 R445
- DOI:
- 10.3969/j.issn.1005-202X.2021.09.023
- Abstract:
- Objective To improve the accuracy of automatic heart segmentation using 2D/3D U-plus-net. Methods The chest
CT images of 60 patients from the First Affiliated Hospital of Zhengzhou University (Data A) and the chest CT images of 45
patients from the First Affiliated Hospital of University of Science and Technology of China (Data B) were collected. A
modified AlexNet was used to divide all CT images into two types, namely heart CT images and no-heart CT images. Based
on the topological structure of 2D/3D U-net, a modified 2D/3D U-plus-net was obtained by reducing network depth,
increasing nodes in a long connection and increasing the convolution number of the decoder. The heart CT images near the
abdomen (the number of CT images was determined by pre-experiment) were input into 3DU-plus-net, while the other heart
CT images were input into 2D U-plus-net. The obtained model was trained and tested by 5-fold cross-validation method.
Finally, the accuracy of automatic heart segmentation was evaluated by Dice coefficient, HD95 and mean surface distance.
Results The Dice coefficient, mean surface distance and HD95 of automatic heart segmentation on Data A were 0.941±
0.012, (3.918±0.201) mm and (5.863±0.561) mm, respectively, while those of automatic heart segmentation on Data B were
0.934±0.014, (4.112±0.320) mm and (6.035±0.659) mm, respectively. Conclusion The automatic segmentation method
based on 2D/3D U-plus-net improves the accuracy of automatic heart segmentation.
Last Update: 2021-09-27