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

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1 PHYSICAL REPLICATION OF HUMAN BONE BY USING DIRECT INTEGRATION OF REVERSE ENGINEERING AND RAPID N. N. Kumbhar 1*, Dr. A. V. Mulay 2, Dr. B. B. Ahuja 3 1 Production Engg. Dept., College of Engineering, Pune , kumbharnn88@gmail.com 2 Production Engg. Dept., College of Engineering, Pune , avm.prod@coep.ac.in 3 Production Engg. Dept., College of Engineering, Pune , bba.prod@coep.ac.in 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. Bio- CAD 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]

PHYSICAL REPLICATION OF HUMAN BONE BY USING DIRECT INTEGRATION OF REVERSE ENGINEERING AND RAPID The first method, where swept blend of curves is involved, this method is extremely complicated, and it

2 PHYSICAL REPLICATION OF HUMAN BONE BY USING DIRECT INTEGRATION OF REVERSE ENGINEERING AND RAPID The first method, where swept blend of curves is involved, this method is extremely complicated, and it cannot be applied without drawing the curve model, since the spline must first be constructed before modeling [4]. In the second method, i. e. marching-cube algorithm technique may make holes and saw-toothed paths within the connection of triangular patches [6]. The third method sufferss from drawbacks in the contour detection for each CT layer and file errors in the construction and use of STL meshes [1]. In this research work a simple but robust process (Delaunay Tetrahadralization) is proposed for converting a 3D point cloud data obtained from 3D Laser scanner machine to a Rapid Prototype physical model. Delaunay Tetrahedralization approach is based on Delaunay Triangulation approach. [7, 8]. 3. Delaunay Triangulation approach Delaunay Triangualtion is a methodology developed so that no vertex from the entire point data set lies inside the circumcircle of any triangle which ensures nonintersecting and non overlapping triangulated network. circumcircle criterion is shown in Figure 1. [8, 9, 10, 11] Figure 2 Circumcircle & Circumsphere criterion 4. Steps followed in Delauany Tetrahedralization approach to develop STL file. To convert this concept into algorithm and then into programming module, following steps are used: [8] 1. Obtain Point cloud data of available product by using 3D Laser scanner. 2. Generate a tetrahedral mesh model of point cloud by using the Delaunay Tetrahedralization approach. 3. Generate triangulated surface mesh model from tetrahedral mesh. 4. Validation of the surface mesh model using Euler s formula, Angle criteria. 5. Generation of STL file. Figure 1 Circumcircle criterion This method has got major limitations like this method is useful only for 2D point cloud data or planer data. But in majority RE projects the product is having curved 3D surfaces. In order to handle 3D data new approach is evolved i. e. Delaunay tetrahedralization based on circumsphere criteria which is shown in Figure 2. Figure 3 Flowchart for conversion of point cloud data into RP model using Delaunay tetrahedralization 189 2

5. Experimental Setup In this research work mainly two machines are used to convert point cloud data into rapid prototyping model and its validation.

superimposed on previously generated STL file to find out the deviation between the two.

3 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 mm to 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 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 Figure 7 Triangulated mesh model of Human Bone To generate an error free STL file, the triangulated mesh model has to be validated by three validation criteria s. 1. Euler s Formula - To check topology. 2. Angle Criterion To check the properties indicating Delaunay triangles. 3. Quality Factor of Triangles - To check aspect ratio

PHYSICAL REPLICATION OF HUMAN BONE BY USING DIRECT INTEGRATION OF REVERSE ENGINEERING AND RAPID This generated mesh model is validated using given criteria s and results are given below in Table 1.

of Triangles (F) 21284 Euler s formula: V E + F = 2 10233 31515 + 21284 = 2 Angle Validation Ok Quality Factor of Triangles 89% Triangles are better size D.

Then to get the deviation between point cloud data and previously generated STL file, a point cloud data is superimposed on the STL file.

4 PHYSICAL REPLICATION OF HUMAN BONE BY USING DIRECT INTEGRATION OF REVERSE ENGINEERING AND RAPID This generated mesh model is validated using given criteria s and results are given below in Table 1. Table 1 Mesh model validation Parameters Human Bone No. of Vertices (V) No. of Edges (E) No. of Triangles (F) Euler s formula: V E + F = = 2 Angle Validation Ok Quality Factor of Triangles 89% Triangles are better size 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 to 0.59 mm. This is an acceptable level. C. Generation of Rapid Prototype model Table 2 shows the development of Rapid Prototyping model form triangulation mesh mode. Table 2 RP model development flow Output model RP machine STL File Format Triangulation Human Bone facet normal outer loop vertex vertex vertex 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 to mm which illustrates the feasibility of this research in medical field

5 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 Vol. 2, No. 4, October [2] Kentaro Iwami and Norihiro Umeda, Advanced Applications of Rapid Prototyping Technology in Modern Engineering, ISBN , (2011) [3] Jelena Milovanović, Miroslav Trajanović, Medical applications of rapid prototyping, Facta Universitatis, Series: Mechanical Engineering Vol. 5, No 1, 2007, pp [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, This work was supported in part by the National Science Council, Taiwan (R.O.C.) under Grant E [5] Timothy S. Newman, Hong Yi, A survey of the marching cubes algorithm, Computers & Graphics 30 (2006) , doi: /j.cag [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) [8] N. N. Kumbhar, A. V. Mulay, B. B. Ahuja Scanned Data Triangulation using Delaunay Tetrahedralization Approach for 3D Point Cloud Data, 4 th International & 25 th All India Manufacturing Technology, Design and Research (AIMTDR ) Conference, Jadhavpur University, Kolkata, India, 14 th 16 th December, 2012, Vol. 1: , ISBM: [9] om/delaunay/delaunay.html [10] y.html [11] delaunay.html [12]

Three-Dimensional Reconstruction for Medical-CAD Modeling

431 Three-Dimensional Reconstruction for Medical-CAD Modeling B. Starly 1 (Binil.Starly@drexel.edu), Z. Fang 1 (zhibin.fang@drexel.edu), W. Sun 1 (sunwei@drexel.edu), A. Shokoufandeh 2 (ashokouf@cs.drexel.edu)