Automatic heart segmentation based on convolutional networks using attention mechanism

Guodong Zhang; Yu Liu; Wei Guo; Wenjun Tan; Zhaoxuan Gong; Muhammad Azaz Farooq

doi:10.1117/12.2643378

12 October 2022 Automatic heart segmentation based on convolutional networks using attention mechanism

Guodong Zhang, Yu Liu, Wei Guo, Wenjun Tan, Zhaoxuan Gong, Muhammad Azaz Farooq

Proceedings Volume 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022); 123421I (2022) https://doi.org/10.1117/12.2643378
Event: Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 2022, Wuhan, China

Abstract

Heart segmentation is challenging due to the poor image contrast of heart in the CT images. Since manual segmentation of the heart is tedious and time-consuming, we propose an attention-based Convolution Neural Network (CNN) for heart segmentation. First, one-hot preprocessing is performed on the multi-tissue CT images. U-Net network with Attention-gate is then applied to obtain the heart region. We compared our method with several CNN methods in terms of dice coefficient. Results show that our method outperforms other methods for segmentation.

Citation Download Citation

Guodong Zhang, Yu Liu, Wei Guo, Wenjun Tan, Zhaoxuan Gong, and Muhammad Azaz Farooq "Automatic heart segmentation based on convolutional networks using attention mechanism", Proc. SPIE 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 123421I (12 October 2022); https://doi.org/10.1117/12.2643378

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