Journal
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
Volume 232, Issue -, Pages -Publisher
ELSEVIER IRELAND LTD
DOI: 10.1016/j.cmpb.2023.107448
Keywords
Image processing; Computational geometry; Visualization; Modeling; Photoacoustics; 3D models; Reconstruction
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This study presents a software tool called EDIT for the visualization and semi-automatic 3D reconstruction of urinary bladder anatomy. The software computes the inner bladder wall using a feedback-based active contour algorithm on ultrasound images and calculates the outer bladder wall by expanding the inner borders on photoacoustic images. Validation was done on phantom objects and in-vivo bladder cancer cases, showing high precision and similarity with true volumes. The EDIT software is a novel tool that extracts different 3D components of the bladder using ultrasound and photoacoustic images.
Background and objective: This study presents the EDIT software, a tool for the visualization of the uri-nary bladder anatomy in the 3D space and for its semi-automatic 3D reconstruction. Methods: The inner bladder wall was computed by applying a Region of Interest (ROI) feedback-based active contour algo-rithm on the ultrasound images while the outer bladder wall was calculated by expanding the inner borders to approach the vascularization area on the photoacoustic images. The validation strategy of the proposed software was divided into two processes. Initially, the 3D automated reconstruction was per-formed on 6 phantom objects of different volume in order to compare the software computed volumes of the models with the true volumes of phantoms. Secondly, the in-vivo 3D reconstruction of the urinary bladder for 10 animals with orthotopic bladder cancer, which range in different stages of tumor progres-sion was performed. Results: The results showed that the minimum volume similarity of the proposed 3D reconstruction method applied on phantoms is 95.59%. It is noteworthy to mention that the EDIT software enables the user to reconstruct the 3D bladder wall with high precision, even if the bladder silhouette has been significantly deformed by the tumor. Indeed, by taking into account the dataset of the 2251 in-vivo ultrasound and photoacoustic images, the presented software performs segmentation with dice similarity 96.96% and 90.91% for the inner and the outer borders of the bladder wall, respec-tively. Conclusions: This study delivers the EDIT software, a novel software tool that uses ultrasound and photoacoustic images to extract different 3D components of the bladder.(c) 2023 Elsevier B.V. All rights reserved.
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