Paper
25 May 2023 Brain image processing based on deep learning neural network
Weihua Tian, Sen Wang, Jiaze Wu, Yizheng Peng, Yongzeng Liang, Shifan Ding, Junyan Liu, Yitong Zhang, Zhenhua Zhan
Author Affiliations +
Proceedings Volume 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022); 126360W (2023) https://doi.org/10.1117/12.2675392
Event: Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2022, Shenyang, China
Abstract
This paper preprocesses four common modes (T1, T1c, T2, Flair) images in clinical brain MRI examination, including image denoising, histogram equalization and offset field correction, and uses convolutional neural network model to segment the image at the pixel level. Compared with the pathologist's manual image segmentation standard, the segmentation accuracy is 95.20%, the F1 coefficient is 0.689, and the Jaccard coefficient is 0.569. Finally, an assistant diagnostic system of automatic segmentation of brain glioma images is designed, which includes a set of UI interface, which is convenient for clinicians and pathologists to use.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Weihua Tian, Sen Wang, Jiaze Wu, Yizheng Peng, Yongzeng Liang, Shifan Ding, Junyan Liu, Yitong Zhang, and Zhenhua Zhan "Brain image processing based on deep learning neural network", Proc. SPIE 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 126360W (25 May 2023); https://doi.org/10.1117/12.2675392
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KEYWORDS
Image segmentation

Education and training

Brain

Deep learning

Neural networks

Neuroimaging

Image processing

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