Scattered data estimation on medical images for cranioplasty applications

Atasoy, Ferhat; Nar, Fatih; Şen, Baha; Ferat, Mahmut

doi:10.1109/siu.2014.6830571

Cited by 1 publication

(8 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Even with large missing region, RBF has variable characterizations that make them well-suited for scattered data interpolation. However, we stated in our previous study [16] that scattered data interpolation generated good results by using RBF if large defected region is not on elliptical regions of a skull. The elliptical region of the skull is given in Fig.…”

Section: A Rbf Based Interpolationmentioning

confidence: 79%

“…This approach is convenient when the problem depends on the multivariate or multi-parameters of scattered data. Besides, it is an appropriate estimation of scattered data in high dimensional space [6], [16], [17].…”

Section: A Rbf Based Interpolationmentioning

confidence: 99%

“…1 is examined carefully, thin-plate spline kernel generates smooth curve. As mentioned in previous published studies, thin-plate spline kernel is wellsuited for cranial defects [6], [16]. In 2D space, RBF method is applied as the following [6], [16], [17]:…”

Section: A Rbf Based Interpolationmentioning

confidence: 99%

“…Proposed Improvement RBF method has been used successfully in previous studies for scattered data interpolation [6], [16], removing an object from image [18] and image inpainting applications [18], [19]. www.ijacsa.thesai.org Carr et al published their study about RBF interpolation for cranioplasty applications.…”

Section: A Rbf Based Interpolationmentioning

confidence: 99%

“…In this study, previously presented scattered data estimation for cranioplasty applications with RBF [16] has been improved. For this purpose, implant shape was created by a mathematical model successfully for high-strength materials such as titanium.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Improvement of Radial basis Function Interpolation Performance on Cranial Implant Design

Atasoy¹,

Şen²,

Nar³

et al. 2017

ijacsa

Self Cite

View full text Add to dashboard Cite

Abstract-Cranioplasty is a neurosurgical operation for repairing cranial defects that have occurred in a previous operation or trauma. Various methods have been presented for cranioplasty from past to present. In computer-aided design based methods, quality of an implant depends on operator's talent. In mathematical model based methods, such as curvefitting and various interpolations, healthy parts of a skull are used to generate implant model. Researchers have studied to improve performance of mathematical models which are independent from operators' talent. In this study, improvement of radial basis function (RBF) interpolation performance using symmetrical data is presented. Since we focused on the improvement of RBF interpolation performance on cranial implant design, results were compared with previous studies involving the same technique. In comparison with previously presented results, difference between the computed implant model and the original skull was reduced from 7 mm to 2 mm using newly proposed approach.

show abstract

Section: A Rbf Based Interpolationmentioning

confidence: 79%