Surface reconstruction for planning and navigation of liver resections. (October 2016)

• Record Type: Journal Article
• Authors: Palomar, Rafael; Cheikh, Faouzi A.; Edwin, Bjørn; Beghdadhi, Azeddine; Elle, Ole J.
• Is Part Of: Computerized medical imaging and graphics. Volume 53(2016)
• Page Start: 30
• Page End: 42
• Publication Date: 2016-10
• Subjects: Surface modeling -- Planning -- Navigation -- Liver resection -- Visualization -- Reconstruction -- Poisson -- Marching Cubes; Diagnostic imaging -- Periodicals; Imaging systems in medicine -- Periodicals; Diagnosis, Radioscopic -- Data processing -- Periodicals; Diagnostic Imaging -- Periodicals; Imagerie pour le diagnostic -- Périodiques; Diagnostic imaging; Periodicals; Electronic journals; Electronic journals; 616.0754
• DOI: 10.1016/j.compmedimag.2016.07.003
• Languages: English
• ISSNs: 0895-6111

Abstract

Abstract : Highlights: Poisson surface reconstruction proposed as method for reconstructing liver surfaces. Better accuracy/complexity trade-off compared to state-of-the-art Marching Cubes. Automated method by best parameter estimation using multi-objective optimization. Same perceived quality (by surgeons) as complex Marching Cubes models. Improved perceived quality (by surgeon) compared to efficient Marching Cubes models. Abstract: Computer-assisted systems for planning and navigation of liver resection procedures rely on the use of patient-specific 3D geometric models obtained from computed tomography. In this work, we propose the application of Poisson surface reconstruction (PSR) to obtain 3D models of the liver surface with applications to planning and navigation of liver surgery. In order to apply PSR, the introduction of an efficient transformation of the segmentation data, based on computation of gradient fields, is proposed. One of the advantages of PSR is that it requires only one control parameter, allowing the process to be fully automatic once the optimal value is estimated. Validation of our results is performed via comparison with 3D models obtained by state-of-art Marching Cubes incorporating Laplacian smoothing and decimation (MCSD). Our results show that PSR provides smooth liver models with better accuracy/complexity trade-off than those obtained by MCSD. After estimating the optimal parameter, automatic reconstruction of liver surfaces using PSR is achieved keeping similar processing time as MCSD. Models from this automatic approach show an average reduction of 79.59% of the polygons compared to the MCSD models presenting similar smoothness properties. Concerning visual quality, on one hand, and despite this reduction in polygons, clinicians perceive the quality of automatic PSR models to be the same as complex MCSD models. On the other hand, clinicians perceive a significant improvement on visual quality for automatic PSR models compared to optimal (obtained in terms of accuracy/complexity) MCSD models. The median reconstruction error using automatic PSR was as low as 1.03 ± 0.23 mm, which makes the method suitable for clinical applications. Automatic PSR is currently employed at Oslo University Hospital to obtain patient-specific liver models in selected patients undergoing laparoscopic liver resection.