Asymmetric edge-aware transformers for monocular endoscopic depth estimation

Ming Wu; Hao Qi; Wenkang Fan; Sunkui Ke; Hui-Qing Zeng; Yinran Chen; Xiongbiao Luo

doi:10.1117/12.3006366

29 March 2024 Asymmetric edge-aware transformers for monocular endoscopic depth estimation

Ming Wu, Hao Qi, Wenkang Fan, Sunkui Ke, Hui-Qing Zeng, Yinran Chen, Xiongbiao Luo

Proceedings Volume 12928, Medical Imaging 2024: Image-Guided Procedures, Robotic Interventions, and Modeling; 129282L (2024) https://doi.org/10.1117/12.3006366
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Conference Poster

Abstract

Monocular depth estimation is a popular task. Due to the difficulty of obtaining true depth labels for the bronchus and the characteristics of the bronchial image such as scarcity of texture, smoother surfaces and more holes, there are many challenges in bronchial depth estimation. Hence, we propose to use a ray tracing algorithm to generate virtual images along with their corresponding depth maps to train an asymmetric encoder-decoder transformer network for bronchial depth estimation. We propose the edge-aware unit to enhance the awareness of the bronchial internal structure considering that the bronchus has few texture features and many edges and holes. And asymmetric encoder-decoder is proposed by us for multi-layer features fusion. The experimental results of the virtual bronchial demonstrate that our method achieves the best results in several metrics, including MAE of 0.915 ± 0.596 and RMSE of 1.471 ± 1.097.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ming Wu, Hao Qi, Wenkang Fan, Sunkui Ke, Hui-Qing Zeng, Yinran Chen, and Xiongbiao Luo "Asymmetric edge-aware transformers for monocular endoscopic depth estimation", Proc. SPIE 12928, Medical Imaging 2024: Image-Guided Procedures, Robotic Interventions, and Modeling, 129282L (29 March 2024); https://doi.org/10.1117/12.3006366

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