Surgical Planning and Additive Manufacturing of an Anatomical Model: A Case Study of a Spine Surgery

Abstract

3D scanning technologies have promising solutions for medical needs such as anatomical models, biocompatible implants, and orthotic/prosthetic models. Although virtual presurgical planning offers more precise results, it may not be applied in every hospital because of the high costs. The aim of this study is to assess the accuracy of the suggested low-cost and effective surgical planning method by means of additive manufacturing to increase success rate of each surgery. In this study, a full spine model of a scoliosis patient was acquired and reconstructed in MIMICS software using different filters and parameters. Therefore, a comparison in terms of geometrical errors among each model was performed based on a reference model. Subsequently, patient-specific full spine model was manufactured using a three-dimensional printing method (fused deposition modeling) and utilized before the surgery. 3D surgical model reconstruction parameters such as wrap tool, binomial blur, and curvature flow filters produced high geometrical errors, while mean filter produced the lowest geometrical error. Furthermore, similarity results of the curvature flow and discrete Gaussian filters were close to mean filter. Smooth tool and mean filter produced almost the same volume of the reference model. Consequently, an ideal protocol for surgical planning of a spine surgery is defined with measurable accuracy. Thus, success rate of a spine surgery may be increased especially for the severe cases owing to the more accurate preoperative review: operability.

Patient Specific Cardiovascular Disease Modelling Based on the Computational Fluid Dynamics Simulations: Segmentation and Hemodynamic Model of a Thoracic Artery

“…Segmentation process was performed using the Thresholding tool at optimized value for target soft tissue (144 -Hounsfield Unit, HU as lower threshold, and 446 HU as higher threshold for this study). These parameters were ideal to obtain exact contour of the target model in a maximum allowable noisy form for this case [22]. Segmentation step was completed after each image section was masked and highlighted by a different color.…”

Investigation of the dimensional accuracy using image processing techniques in powder bed fusion

“…In the mean filtering method, using the created kernel matrix, arithmetic, harmonic or geometric averages of the pixel are taken, and a new pixel value is determined. 26 The mathematical expression of arithmetic, geometric, and the harmonic mean filter is given in equations ( 1 Median filter. A median filter is a non-linear filter method used to reduce the noise on the image.…”