3-D and 2-D reconstruction of bladders for the assessment of inter-session detection of tissue changes: a proof of concept

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 0-0.79 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.

Keywords: 3-D reconstruction; Bladder; Computer vision; Monocular; Proof of concept.

Fig. 1

Impressions of state-of-art approaches. a Suarez-Ibarrola et al. [7]. b Falcon et al. [8]. c Lurie et al. [9]. d Ben-Hamadou et al. [10]. e Kriegmair et al. [11]. f Shevchenko et al. [12]. g Soper et al. [13]. h Phan et al. [14]

Fig. 2

Workflow for in vivo bladder reconstruction. Cystoscopy videos of sessions are converted to 3-D textured models and 2-D atlases, which can be compared visually

Fig. 3

Alternate workflow for the textured bladder phantom. 3-D textured models and 2-D atlases are reconstructed and co-registered. Changes between successive sessions are automatically detected and highlighted

Fig. 4

3-D reconstruction of in vivo bladder (post-op)

Fig. 5

Post-operative atlas of in vivo bladder, with the tumor surgically removed

Fig. 6

Pre-operative atlas of in vivo bladder. A tumor can be seen at the right side

Fig. 7

Atlas of bladder phantom in first session

Fig. 8

Atlas of bladder phantom in second session, after adding six stickers representing tumors

Fig. 9

Difference of atlases of phantom in two successive sessions. The 50% gray color represents areas which remained unchanged (i.e., identical pixel color) between the sessions. Deviations from 50% gray corresponding to proportionally larger changes in pixel color. Various brightly colored areas of various sizes can be distinguished

Fig. 10

Atlas of second session, with highlighted areas indicating significant texture changes between the two sessions

Fig. 11

3-D rendering of bladder phantom (second session), with texture changes highlighted