physical replication of human bone by using direct ... - IIT Guwahati

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Dec 12, 2014 - two modern computer-based technologies, reverse engineering (RE) and rapid prototyping (RP). The method is multipurpose and can be used ...
5th International & 26th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2014) December 12th–14th, 2014, IIT Guwahati, Assam, India

 

PHYSICAL REPLICATION OF HUMAN BONE BY USING DIRECT INTEGRATION OF REVERSE ENGINEERING AND RAPID PROTOTYPING TECHNIQUES N. N. Kumbhar1*, Dr. A. V. Mulay2, Dr. B. B. Ahuja3 1

Production Engg. Dept., College of Engineering, Pune - 411005, [email protected]

2

Production Engg. Dept., College of Engineering, Pune - 411005, [email protected]

3

Production Engg. Dept., College of Engineering, Pune - 411005, [email protected] Abstract:

The replication of an existing object of complex shape is one of the typical applications of the integration between two modern computer-based technologies, reverse engineering (RE) and rapid prototyping (RP). The method is multipurpose and can be used in various applicative domains like mechanical components, house hold equipments, bio-medical, anatomical parts amongst others. This paper presents a process to construct 3D rapid prototyping (RP) physical models of human bone by using 3D point cloud data which is obtained from 3D laser scanner. This process is achieved by generating the triangular mesh directly from 3D point cloud data without developing any surface model using any commercial CAD software. The generated STL file from 3D point cloud data is used as a basic input for RP process. The Delaunay Tetrahadralization approach is used to process the 3D point cloud data to obtain STL file. 3D point cloud data of Metacarpus (human Bone) is used as the case study for the generation of the 3D RP model. Once this STL file is obtained, a 3D physical model of the human bone is generated on Rapid Prototyping machine and its virtual reality model is presented for visualization in STL format. The results of this research are assessed for clinical reliability in replication of human bone in medical field. Key words: Reverse Engineering, Rapid Prototyping, 3D Point Cloud Data, Delaunay Tetrahedralization, STL file, Human bone.

1. Introduction: Bio-medical engineering is a technological field with great potential for future advances. This field encompasses medical treatment engineering, genetic technology and medicine engineering. Building sets of medical information, medical images, bio-medical materials and applying these sets of medical data assists in the development of all aspects of biomedical engineering [1, 2]. In recent years, CAD has been increasingly applied in bio-medical engineering. The integration of CAD and medical technology is referred to as Bio-CAD. BioCAD includes regenerative medicine engineering, computer-aided surgery, structural modeling of tissue, design of orthopedic devices and implants, reverse engineering (RE), 3D reconstruction and solid freeform fabrication or bio-manufacturing [2]. CT medical imaging is the key tool for viewing the internal structure of the human body, but is limited by its 2D image presentation in that it does not allow doctors to quickly diagnose illnesses and explain symptoms and treatments to patients [3]. Medical

images in 3D solid models are therefore very important in the diagnosis and treatment process. All reconstructed 3D solid models can be converted to RP physical models (STL file). A number of open sources and commercial products for 3D biomechanical construction are available, but still, these tools does not appear to be a simple and accurate for bio image acquisition and analysis.

2. Methods to construct STL file: There are three methods that can be applied to reconstruct a 3D solid model of bio-medical imaging from its 2D CT image or 3D point cloud data. The first method involves a swept blend from the contours of each layer in point data [4]. The second method is via marching-cube algorithm [5, 6]. With the third method, contour detection in each layer is used to construct the mixed layers in the triangular STL model for RP fabrication by connecting the vertices of two parallel polygons [1]. Each of these methods has disadvantages [1, 4, 5, 6].

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PHYSICAL REPLICATION OF HUMAN BO ONE BY USING G DIRECT INTEG GRATION OF REVERSE R ENGIN NEERING AND RAPID ES PROTOTYPIING TECHNIQUE

The fiirst method, where w swept bllend of curvess is involved, this t method iss extremely coomplicated, andd it cannot be applied witho out drawing the t curve moddel, since the spline must first be constructed beffore [ In the seco ond method, i.e. marching-cuube modeling [4]. algorithm technique may y make holes and saw-toothhed paths withhin the connecction of trianggular patches [6]. [ The third method m sufferss from drawbaccks in the contoour detection for each CT layer and fiile errors in the constructioon and use of STL S meshes [1]]. In thiss research worrk a simple buut robust proccess (Delaunay Tetrahadrallization) is proposed for convertingg a 3D point cloud data obbtained from 3D Laser scannner machine to a Rapid Prrototype physiical model. Deelaunay Tetrah hedralization appproach is based on Delaunaay Triangulatio on approach. [77, 8].

3. Delaaunay Trian ngulation ap pproach Delaunnay Triangu ualtion is a methodoloogy developed so that no veertex from the entire point data d set lies inside the circu umcircle of anny triangle whhich ensures nonintersectin ng and noon overlapping triangulateed network. cirrcumcircle criteerion is shownn in Figure 1. [8, [ 9, 10, 11]

Figurre 2 Circumciircle & Circum msphere criterrion

4. Stteps folllowed i in Delauany Teetrahedralizzation apprroach to devvelop ST TL file. To connvert this conccept into algorrithm and then into program mming module, following steps are used: [88] 1. Obtain Point clooud data of avvailable produuct by using 3D Laser scanner. s 2. Gennerate a tetrahhedral mesh model m of point cloud byy using thee Delaunay Tetrahedraliization appproach. 3. Gennerate trianguulated surface mesh model from tettrahedral meshh. 4. Vallidation of the surface mesh model using Euler’s E forrmula, Angle criteria. c 5. Genneration of ST TL file.

Figure 1 Circumcircle critterion m has got g major limitations like this t This method method is useful only for 2D point clooud data or plaaner data. But in i majority RE E projects the product p is havving curved 3D D surfaces. In order to handdle 3D data new n approach is evolved i.e. Delaunay tetrahedralizattion based on circumsphere crriteria which iss shown in Figgure 2.

Figurre 3 Flowcharrt for conversiion of point clooud data into RP P model usingg Delaunay tetrrahedralizatioon

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5th International & 26th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2014) December 12th–14th, 2014, IIT Guwahati, Assam, India

 

5. Experimental Setup In this research work mainly two machines are used to convert point cloud data into rapid prototyping model and its validation. The first machine used is RP machine which is manufactured by stratasys Ltd. This machine is based on FDM technology which maintains layer thickness of 0.254 mm to 0.500 mm, shown in Figure 4.

superimposed on previously generated STL file to find out the deviation between the two. Initially the source code is developed to convert point cloud data in to STL file using Delaunay Tetrahedralization. To check the proper working of source code initially simple example of rhombus containing 8 points is considered [8] and after getting satisfactory results the same program is used to convert the point cloud data of Metacarpals (Human Bone) in to STL file. This case study is divided in to five stages. 1. Data acquisition 2. Mesh constriction 3. Validation of STL file 4. Generation of RP model 5. Physical Validation

Case Study

Figure 4 Rapid Prototyping machine

A. Data Acquisition: In this case study point cloud data is directly available. Hence this step is eliminated. Total points used for conversion are 10233, which are shown in Figure 6.

Second machine is PICZA 3D Laser Scanner LPX 600 is used to scan the physical object. The output obtained from this is expressed in terms of a cloud of points, or set of points with coordinates x,y,z in a Cartesian reference system, which is also shown in Figure 5. Figure 6 Bone Point Cloud Data B. Mesh construction To get triangulated mesh model of obtained point cloud data, Delaunay Tetrahedralization approach is used, mesh model is shown in Figure 7.

Figure 5 PICZA 3D Laser Scanner LPX 600 Figure 7 Triangulated mesh model of Human Bone

6. Case Study and Analysis This research proposes Delanunay tetrahedralization mesh generation of 3D point cloud data to get physical replication of human bone. There are three main steps involved in the replication process: Scanning of model, mesh generation (STL file generation) and rapid manufacturing by RP machine. To do the physical validation of generated RP product, the RP product is re - scanned by 3D Laser Scanner and then re scanned point cloud data is

To generate an error free STL file, the triangulated mesh model has to be validated by three validation criteria’s. 1. 2. 3.

Euler’s Formula - To check topology. Angle Criterion – To check the properties indicating Delaunay triangles. Quality Factor of Triangles - To check aspect ratio.

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PHYSICAL REPLICATION OF HUMAN BONE BY USING DIRECT INTEGRATION OF REVERSE ENGINEERING AND RAPID PROTOTYPING TECHNIQUES

This generated mesh model is validated using given criteria’s and results are given below in Table 1. Table 1 Mesh model validation Parameters No. of Vertices (V) No. of Edges (E) No. of Triangles (F) ‫ ׵‬Euler’s formula: V–E+F=2 Angle Validation Quality Factor of Triangles

Human Bone 10233 31515 21284

D. Physical Validation To do the physical validation of the RP product, the RP product is re - scanned by 3D Laser Scanner. Then to get the deviation between point cloud data and previously generated STL file, a point cloud data is superimposed on the STL file. The analyzed results are shown in Figure 8 with the differences within ±0.5 mm. The human bone has a difference of + 0.37 to – 0.59 mm. This is an acceptable level.

10233 – 31515 + 21284 = 2 Ok 89% Triangles are better size

C. Generation of Rapid Prototype model Table 2 shows the development of Rapid Prototyping model form triangulation mesh mode.

Triangulation

Table 2 RP model development flow

Output model

RP machine

STL File Format

Human Bone facet normal 8.66 -0.00 5.00 outer loop vertex 1.00 1.00 1.73 vertex 2.00 0.00 0.00 vertex 2.00 2.00 0.00 endloop endfacet

Figure 8 Comparison result of Human Bone

7. Conclusion The research work described the possibility of applying both Reveres engineering and Rapid Prototyping techniques in the medical field. In the specific case of reproduction of a human bone, a point cloud data is processed by using commercial software to develop a solid model and rapid prototyping model, but it is time consuming process. To overcome time consuming process a Delaunay Tetrahadralization approach is used to generate a rapid prototype model, which gives good results after physical validation. Comparison between the generated model and the original was satisfactory. This research suggested three steps to generate the model without complexity: first, data acquisition through 3D Laser scanner; second, Mesh generation by using Delaunay Tetrahadralization and third is RP model generation. Using analysis and comparison method, it can be shown that the method used in this research is within an acceptable error range. The error range is consistently around + 0.37 to -0.59 mm which illustrates the feasibility of this research in medical field.

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5th International & 26th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2014) December 12th–14th, 2014, IIT Guwahati, Assam, India

 

8. Reference [1] Jagtap Suraj Rajendra, Analysis of integration of reverse engineering and generative manufacturing processes for medical science – A review, Int. J. Mech. Eng. & Rob. Res. 2013, ISSN 2278 – 0149 www.ijmerr.com, Vol. 2, No. 4, October 2013. [2] Kentaro Iwami and Norihiro Umeda, Advanced Applications of Rapid Prototyping Technology in Modern Engineering, ISBN 978-953-307-698-0, (2011)www.intechopen.com. [3] Jelena Milovanović, Miroslav Trajanović, Medical applications of rapid prototyping, Facta Universitatis, Series: Mechanical Engineering Vol. 5, No 1, 2007, pp. 79 – 85. [4] C.S. Wang, C.Y. Hsiao, T.R. Chang, and C.K. Teng, STL Mesh Reconstruction for Bio-Medical Rapid Prototyping Model, Manuscript received March 15, 2007. This work was supported in part by the National Science Council, Taiwan (R.O.C.) under Grant 93-2213-E-029-022. [5] Timothy S. Newman, Hong Yi, A survey of the marching cubes algorithm, Computers & Graphics 30 (2006) 854–879, doi:10.1016/j.cag.2006.07.021 [6] Thomas Wiemann, Andres N¨uchter, Kai Lingemann, Stefan Stiene, and Joachim Hertzberg, Automatic Construction of Polygonal Maps From

Point Cloud Data, The Institute of Computer Science, University of Osnabr¨uck, Germany (2011) [7] Seok-Hee Lee, Ho-Chan Kim, Sung-Min Hur, Dong-Yol Yang, STL file generation from measured point cloud data by segmentation and Delaunay Trinagulation, Computer – Aided Design 34 (2002) 691 – 704. [8] N. N. Kumbhar, A. V. Mulay, B. B. Ahuja “Scanned Data Triangulation using Delaunay Tetrahedralization Approach for 3D Point Cloud Data”, 4th International & 25th All India Manufacturing Technology, Design and Research (AIMTDR - 2012) Conference, Jadhavpur University, Kolkata, India, 14th – 16th December, 2012, Vol. 1: 643 – 648, ISBM: 978 – 93 – 82062 – 75 – 2. [9] http://goanna.cs.rmit.edu.au/~gl/research/comp_ge om/delaunay/delaunay.html [10] http://www.ics.uci.edu/~eppstein/gina/delauna y.html [11] http://www.cse.unsw.edu.au/~lambert/java/3d/ delaunay.html [12] http://www.stratasys.com/3d-printers/designseries/performance/dimension-elite

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