The overview of the deep learning integrated into the medical imaging of liver: a review

被引:0
|
作者
Kailai Xiang
Baihui Jiang
Dong Shang
机构
[1] First Affiliated Hospital of Dalian Medical University,Department of General Surgery
[2] First Affiliated Hospital of Dalian Medical University,Clinical Laboratory of Integrative Medicine
[3] First Affiliated Hospital of Dalian Medical University,Department of Ophthalmology
来源
Hepatology International | 2021年 / 15卷
关键词
Deep learning; Artificial intelligence; Convolutional neural network; Liver disease; Ultrasonography; Computed tomography; Magnetic resonance imaging; Imaging diagnosis; Image segmentation; Lesion classification;
D O I
暂无
中图分类号
学科分类号
摘要
Deep learning (DL) is a recently developed artificial intelligent method that can be integrated into numerous fields. For the imaging diagnosis of liver disease, several remarkable outcomes have been achieved with the application of DL currently. This advanced algorithm takes part in various sections of imaging processing such as liver segmentation, lesion delineation, disease classification, process optimization, etc. The DL optimized imaging diagnosis shows a broad prospect instead of the pathological biopsy for the advantages of convenience, safety, and inexpensiveness. In this paper, we reviewed the published representative DL-related hepatic imaging works, described the general situation of this new-rising technology in medical liver imaging and explored the future direction of DL development.
引用
收藏
页码:868 / 880
页数:12
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