Magnetic Resonance Imaging Brain Tumor Image Segmentation Based on Improved U-Net

Haiwei Mu; Ying Guo; Xinghui Quan; Zhimin Cao; Jian Han

doi:10.3788/LOP202158.0410022

Journals >Laser & Optoelectronics Progress >Volume 58 >Issue 4 >Page 0410022 > Article

Laser & Optoelectronics Progress
Vol. 58, Issue 4, 0410022 (2021)

Magnetic Resonance Imaging Brain Tumor Image Segmentation Based on Improved U-Net

Haiwei Mu^1、2, Ying Guo^1、2, Xinghui Quan^1、2、*, Zhimin Cao^1、2, and Jian Han^1、2

Author Affiliations

¹School of Physics and Electrical Engineering, Northeast Petroleum University, Daqing, Heilongjiang 163318, China

²Research and Development Center for Testing and Measurement Technology and Instrumentation, Heilongjiang Province Universities, Northeast Petroleum University, Daqing, Heilongjiang 163318, China

show less

DOI: 10.3788/LOP202158.0410022 Cite this Article Set citation alerts

Haiwei Mu, Ying Guo, Xinghui Quan, Zhimin Cao, Jian Han. Magnetic Resonance Imaging Brain Tumor Image Segmentation Based on Improved U-Net[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0410022 Copy Citation Text

show less

Cited By

Article index updated: May. 27, 2024

Citation counts are provided from Researching.

The article is cited by 8 article(s) from Researching.

Haiwei Mu, Ying Guo, Xinghui Quan, Zhimin Cao, Jian Han. Magnetic Resonance Imaging Brain Tumor Image Segmentation Based on Improved U-Net[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0410022

Download Citation

Set citation alerts for the article

Tools

Set citation alerts for the article

Save the article for my favorites

Paper Information