Feasibility of differential geometry-based features in detection of anatomical feature points on patient surfaces in range image-guided radiation therapy

Soufi, Mazen; Arimura, Hidetaka; Nakamura, Katsumasa; Lestari, Fauzia P.; Haryanto, Freddy; Hirose, Taka aki; Yoshiyuki, Umedu; Shioyama, Yoshiyuki; Fukai, Tomoki

doi:10.1007/s11548-016-1436-x

Cited by 5 publications

(2 citation statements)

References 32 publications

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“…The method can be tracked back to early studies, reporting registration of a CT‐segmentation to traces of points, intraoperatively acquired with ultrasound. Curvature‐based features in stereo reconstructions from range and ToF images were detected and described through differential geometry and B‐spline approximation for an improved accuracy and temporal stability in image‐guided radiation therapy …”

Section: Introductionmentioning

confidence: 99%

Vector field analysis for surface registration in computer‐assisted ENT surgery

Diakov

Freysinger

2019

Robotics Computer Surgery

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Background Manual paired‐point registration for navigated ENT‐surgery is prone to human errors; automatic surface registration is often caught in local minima. Methods Anatomical features of the human occiput are integrated into an algorithm for surface registration. A vector force field is defined between the patient and operating room datasets; registration is facilitated through gradient‐based vector field analysis optimization of an energy function. The method is validated exemplarily on patient surface data provided by a mechanically positioned A‐mode ultrasound sensor. Results Successful registrations were achieved within the entire parameter space, as well as from positions of local minima that were found by the Gaussian fields algorithm for surface registration. Sub‐millimetric registration error was measured in clinically relevant anatomical areas on the anterior skull and within the generally accepted margin of 1.5 mm for the entire head. Conclusion The satisfactory behavior of this approach potentially suggests a wider clinical integration.

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Section: Introductionmentioning

confidence: 99%

Vector field analysis for surface registration in computer‐assisted ENT surgery

Diakov

Freysinger

2019

Robotics Computer Surgery

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“…Application areas include computer graphics and visualization, healthcare, seismology, computational archaeology [Du18], etc. For example, curvature has been used in segmentation, object recognition, geometric modeling, and analysis of images and volumes [Bib16,Bes86,Bel12,Bag16,Lef18,Sou16], to perform reconstruction in images [Lef17], for biometrics [Sya17], for computer vision-based quality control in manufacturing [Kot18], etc. Other examples include emphasizing features in renderings of meshes [AR18] and images [Hau18], mesh parameterization [Vin17], highlighting shapes in volume renderings [Kin03], and visualization of medical data [Pre16].…”

Section: Introductionmentioning

confidence: 99%

Exhibition and Evaluation of Two Schemes for Determining Hypersurface Curvature in Volumetric Data

Hauenstein

Newman

2019

JWSCG

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Advancements in methodologies for determining 3-dimensional manifold (hypersurface) curvature in volumetric data are presented. Such determinations are requisite in certain shape-based visualization and analysis tasks. The methods explored here are convolution-based approaches. In addition to motivating and describing these methods, an evaluation of their (1) accuracy and (2) computational performance is also presented. That evaluation includes benchmarking on both noise-free and noisy volumetric data.

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