Combined Channel and Spatial Attention-Based Stereo Endoscopic Image Super-Resolution
Issued Date
2023-01-01
Resource Type
ISSN
21593442
eISSN
21593450
Scopus ID
2-s2.0-85179523588
Journal Title
IEEE Region 10 Annual International Conference, Proceedings/TENCON
Start Page
920
End Page
925
Rights Holder(s)
SCOPUS
Bibliographic Citation
IEEE Region 10 Annual International Conference, Proceedings/TENCON (2023) , 920-925
Suggested Citation
Hayat M., Armvith S., Achakulvisut T. Combined Channel and Spatial Attention-Based Stereo Endoscopic Image Super-Resolution. IEEE Region 10 Annual International Conference, Proceedings/TENCON (2023) , 920-925. 925. doi:10.1109/TENCON58879.2023.10322331 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/91569
Title
Combined Channel and Spatial Attention-Based Stereo Endoscopic Image Super-Resolution
Author(s)
Author's Affiliation
Other Contributor(s)
Abstract
Stereo Imaging technology integration into medical diagnostics and surgeries brings a great revolution in the field of medical sciences. Now, surgeons and physicians have better insight into the anatomy of patients' organs. Like other technologies, stereo cameras have limitations, e.g., low resolution (LR) and blurry output images. Currently, most of the proposed techniques for super-resolution focus on developing complex blocks and complicated loss functions, which cause high system complexity. We proposed a combined channel and spatial attention block to extract features incorporated with a specific but very strong parallax attention module (PAM) for endoscopic image super-resolution. The proposed model is trained using the da Vinci dataset on scales 2 and 4. Our proposed model has improved PSNR up to 2.12 dB for scale 2 and 1.29 dB for scale 4, while SSIM is improved by 0.03 for scale 2 and 0.0008 for scale 4. By incorporating this method, diagnosis and treatment for endoscopic images can be more accurate and effective.