The accuracy of solid model and rapid prototype of prostheses in comparison to the digital CT image data

Prostheses are a derivative of biomedical products that have important things, which are: a design, size and bio compatible material. To produce optimum prostheses, safe and comfortable use, it would require design a model that fits the size of the patient’s anatomy. In this paper describes the accuracy of solid model and rapid prototype of prostheses in comparison to the digital CT image data. Where the main parameters used as the reference measurement is digital CT image data. The data were analyzed using a statistical method to get the standard deviation of the comparison parameters of the data obtained, so that it can be known how the accuracy of the measurement results of each data.

[1]  A. Lombardi,et al.  Why are total knees failing today? Etiology of total knee revision in 2010 and 2011. , 2013, The Journal of arthroplasty.

[2]  Kunwoo Lee,et al.  Principles of CAD/CAM/CAE Systems , 1999 .

[3]  Gandjar Kiswanto,et al.  Research – Design & Development of Fast Customized Manufacturing for Prostheses TKR Based on Rapid Prototyping , 2014 .

[4]  Syed H. Masood,et al.  Design and fabrication of reconstructive mandibular models using fused deposition modeling , 2008 .

[5]  D. Dimitrov,et al.  Advances in three dimensional printing – state of the art and future perspectives , 2006 .

[6]  Josef Hoschek,et al.  Handbook of Computer Aided Geometric Design , 2002 .

[7]  Barry Berman,et al.  3D printing: the new industrial revolution , 2012, IEEE Engineering Management Review.

[8]  Freddie H. Fu,et al.  Gene Therapy in the Treatment of Knee Disorders , 2012 .

[9]  Sharon E Hohler,et al.  Total knee arthroplasty: past successes and current improvements. , 2008, AORN journal.

[10]  Giorgio Olmi,et al.  Experimental characterization and analytical modelling of the mechanical behaviour of fused deposition processed parts made of ABS-M30 , 2013 .

[11]  Ho-Chan Kim,et al.  STL file generation from measured point data by segmentation and Delaunay triangulation , 2002, Comput. Aided Des..

[12]  Yuqi Pan,et al.  The use of CT scan and stereo lithography apparatus technologies in a canine individualized rib prosthesis. , 2014, International journal of surgery.

[13]  K. Leong,et al.  Rapid Prototyping: Principles and Applications (with Companion CD-ROM) , 2003 .

[14]  Lee-Ing Tong,et al.  Optimizing processes based on censored data obtained in repetitious experiments using grey prediction , 2005 .

[15]  K. Saleh,et al.  Periprosthetic fractures complicating total knee arthroplasty , 2003 .

[16]  Hong-Tzong Yau,et al.  Extension of surface reconstruction algorithm to the global stitching and repairing of STL models , 2003, Comput. Aided Des..

[17]  D. Biau,et al.  Comparative study of intraoperative knee flexion with three different TKR designs. , 2010, Orthopaedics & traumatology, surgery & research : OTSR.

[18]  H Ramm,et al.  Computed tomography analysis of knee pose and geometry before and after total knee arthroplasty. , 2012, Journal of biomechanics.

[19]  Clare K. Fitzpatrick,et al.  THE ROLE OF PATIENT, SURGICAL, AND IMPLANT DESIGN VARIATIONS IN TKR PERFORMANCE , 2012 .

[20]  Farid Amirouche,et al.  Challenges in modeling total knee arthroplasty and total hip replacement , 2011 .

[21]  A. Tanavalee,et al.  Anthropometric measurements of knee joints in Thai population: correlation to the sizing of current knee prostheses. , 2011, The Knee.

[22]  Stefan Lohfeld,et al.  Engineering Assisted Surgery™: A route for digital design and manufacturing of customised maxillofacial implants , 2007 .