Abstract
Purpose: Abnormalities in the bladder wall require careful investigation regarding type, spatial position and invasiveness. Construction of a 3-D model of the bladder is helpful to ensure adequate coverage of the scanning procedure, quantitative comparison of bladder wall textures between successive sessions and finding back previously-discovered abnormalities.
Methods: Videos of both an in-vivo bladder and a textured bladder phantom were acquired. Structure-from-motion and bundle adjustment algorithms were used to construct a 3-D point cloud, approximate it by a surface mesh, texture it with the back-projected camera frames and draw the corresponding 2-D atlas. Reconstructions of successive sessions were compared; those of the bladder phantom were co-registered, transformed using 3-D thin plate splines and post-processed to highlight significant changes in texture.
Results: The reconstruction algorithms of the presented workflow were able to construct 3-D models and corresponding 2-D atlas of both the in-vivo bladder and the bladder phantom. For the in-vivo bladder the portion of the reconstructed surface area was 58% and 79% for the pre- and post-operative scan, respectively. For the bladder phantom the full surface was reconstructed and the mean reprojection error was 0.081 mm (range 0 mm - 0.79 mm). In inter-session comparison the changes in texture were correctly indicated for all six locations.
Conclusion: The proposed proof-of-concept was able to perform 3-D and 2-D reconstruction of an in-vivo bladder wall based on a set of monocular images. In a phantom study the computer vision algorithms were also effective in co-registering reconstructions of successive sessions and highlighting texture changes between sessions. These techniques may be useful for detecting, monitoring and revisiting suspicious lesions.
Methods: Videos of both an in-vivo bladder and a textured bladder phantom were acquired. Structure-from-motion and bundle adjustment algorithms were used to construct a 3-D point cloud, approximate it by a surface mesh, texture it with the back-projected camera frames and draw the corresponding 2-D atlas. Reconstructions of successive sessions were compared; those of the bladder phantom were co-registered, transformed using 3-D thin plate splines and post-processed to highlight significant changes in texture.
Results: The reconstruction algorithms of the presented workflow were able to construct 3-D models and corresponding 2-D atlas of both the in-vivo bladder and the bladder phantom. For the in-vivo bladder the portion of the reconstructed surface area was 58% and 79% for the pre- and post-operative scan, respectively. For the bladder phantom the full surface was reconstructed and the mean reprojection error was 0.081 mm (range 0 mm - 0.79 mm). In inter-session comparison the changes in texture were correctly indicated for all six locations.
Conclusion: The proposed proof-of-concept was able to perform 3-D and 2-D reconstruction of an in-vivo bladder wall based on a set of monocular images. In a phantom study the computer vision algorithms were also effective in co-registering reconstructions of successive sessions and highlighting texture changes between sessions. These techniques may be useful for detecting, monitoring and revisiting suspicious lesions.
Original language | English |
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Pages (from-to) | 1915-1924 |
Number of pages | 10 |
Journal | International journal of computer assisted radiology and surgery |
Volume | 18 |
Early online date | 21 Apr 2023 |
DOIs | |
Publication status | Published - Oct 2023 |
Keywords
- UT-Hybrid-D
- Bladder
- Computer vision
- Monocular
- 3-D reconstruction
- Proof of concept