Bai, L;
Chen, T;
Tan, Q;
Nah, WJ;
Li, Y;
He, Z;
Yuan, S;
... Ren, H; + view all
(2024)
EndoUIC: Promptable Diffusion Transformer for Unified Illumination Correction in Capsule Endoscopy.
In:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2024.
(pp. pp. 296-306).
Springer: Cham, Switzerland.
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Abstract
Wireless Capsule Endoscopy (WCE) is highly valued for its non-invasive and painless approach, though its effectiveness is compromised by uneven illumination from hardware constraints and complex internal dynamics, leading to overexposed or underexposed images. While researchers have discussed the challenges of low-light enhancement in WCE, the issue of correcting for different exposure levels remains underexplored. To tackle this, we introduce EndoUIC, a WCE unified illumination correction solution using an end-to-end promptable diffusion transformer (DiT) model. In our work, the illumination prompt module shall navigate the model to adapt to different exposure levels and perform targeted image enhancement, in which the Adaptive Prompt Integration (API) and Global Prompt Scanner (GPS) modules shall further boost the concurrent representation learning between the prompt parameters and features. Besides, the U-shaped restoration DiT model shall capture the long-range dependencies and contextual information for unified illumination restoration. Moreover, we present a novel Capsule-endoscopy Exposure Correction (CEC) dataset, including ground-truth and corrupted image pairs annotated by expert photographers. Extensive experiments against a variety of state-of-the-art (SOTA) methods on four datasets showcase the effectiveness of our proposed method and components in WCE illumination restoration, and the additional downstream experiments further demonstrate its utility for clinical diagnosis and surgical assistance. The code and the proposed dataset are available at github.com/longbai1006/EndoUIC.
| Type: | Proceedings paper |
|---|---|
| Title: | EndoUIC: Promptable Diffusion Transformer for Unified Illumination Correction in Capsule Endoscopy |
| Event: | Medical Image Computing and Computer Assisted Intervention – MICCAI 2024: 27th International Conference |
| ISBN-13: | 9783031721038 |
| DOI: | 10.1007/978-3-031-72104-5_29 |
| Publisher version: | https://doi.org/10.1007/978-3-031-72104-5_29 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10203065 |
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