R_Bibb_Medical_Modelling_The_Application_of_Adv.pdf

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Working with medical scan data 57 4.22 The effect of the number of control points on IGES patch quality, (from top) 6 control points, 10 control points, 20 control points and 100 control points.
58 Medical modelling scan data of a human hip with control points varying from 6 to 100. The areas of darker grey show where the IGES surface patch closely approximates the scan surface whilst the lighter areas show that the IGES surface patch is below the scanned surface. The IGES surface patch is also shown as a mesh showing the complexity of the surface as the number of control points increases. Depending on the software being used, the quality of the fi t between the IGES surface and the original data can be visually inspected on screen as shown in Fig. 4.22 or numerically quantifi ed. For the surface with only six control points, the average gap between original surface and the IGES patch is 0.818 mm. In comparison, the surface shown with 100 control points is a much closer fi t with the average gap almost negligible at 0.00678 mm. As NURBS surfaces are controlled by mathematical equations, the patches themselves have to obey certain criteria in order for the equations to solve. Failure to obey these constraints will result in no surface patch being generated or a patch that fl ips, creases or twists. Typically, surfaces that exhibit these faults cannot be physically manufactured or they give rise to other problems. To create solid models from surface patches, all of the surface area of the object must be covered by NURBS patches. In addition, the patches must meet at common edges and not overlap. These surfaces can then be ‘stitched’ together to form a true three-dimensional solid computer model of the object.
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Medical modelling
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Medical modelling The application o
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Contents Preface ix Acknowledgement
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Contents vii 6.10 Rehabilitation ap
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x Preface Therefore, it is hoped th
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1.1 Background 1 Introduction The p
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Introduction 3 Whilst this book is
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Long axis 1.1 The anatomical positi
Page 20 and 21: Introduction 7 1.3 The major refere
Page 22 and 23: Medical imaging for rapid prototypi
Page 26 and 27: 2.2.3 Anatomical coverage Medical i
Page 30 and 31: 2.6 X-ray scatter artefact in a CT
Page 32 and 33: 2.9 Close up of noise. Medical imag
Page 34 and 35: 2.12 Smooth data. Medical imaging f
Page 40 and 41: 1 Medical imaging for rapid prototy
Page 46 and 47: Export data format and media 33 (NE
Page 48 and 49: 3.3 Media Export data format and me
Page 50 and 51: 4.1 Pixel data operations 4 Working
Page 52 and 53: 4.3 Effect of a high threshold. 4.4
Page 54 and 55: Working with medical scan data 41 4
Page 58 and 59: Working with medical scan data 45 S
Page 60 and 61: 4.4 Two-dimensional formats Working
Page 64 and 65: Working with medical scan data 51 I
Page 66 and 67: 4.18 Close up view showing facets.
Page 72 and 73: 5.1 Background to rapid prototyping
Page 74 and 75: Physical reproduction 61 developing
Page 76 and 77: Physical reproduction 63 will displ
Page 78 and 79: Physical reproduction 65 As there i
Page 80 and 81: Physical reproduction 67 However, t
Page 82 and 83: Data quality Physical reproduction
Page 84 and 85: Physical reproduction 71 In some ca
Page 86 and 87: Physical reproduction 73 Overhangin
Page 88 and 89: Physical reproduction 75 5.10 SL mo
Page 90 and 91: Physical reproduction 77 5.12 Selec
Page 92 and 93: 5.13 A Perfactory ® model of a man
Page 94 and 95: 5.15 FDM TM model of the mandible.
Page 96 and 97: Table 5.3 Advantages and disadvanta
Page 98 and 99: Physical reproduction 85 In medical
Page 100 and 101: Table 5.5 Advantages and disadvanta
Page 102 and 103: 5.7 Jetting head technology 5.7.1 P
Page 104 and 105: 5.23 ThermoJet ® model of the mand
Page 106 and 107: 5.24 LOM TM model of the mandible.
Page 108 and 109: 5.26 LOM TM model of a partial face
Page 110 and 111: 6 Case studies The following case s
Page 112 and 113: IMPLEMENTATION 6.1 Implementation c
Page 114 and 115: Post model Hospital department Pati
Page 116 and 117: Case studies 103 When using this so
Page 118 and 119: Case studies 105 (Mimics). Image ma
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Case studies 107 full co-operation
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Case studies 109 communication and
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• to achieve patient’s agreemen
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6.2.4 Rapid prototyping technologie
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Case studies 115 not be suitable. A
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Case studies 117 scale of the data
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6.7 SL model with signifi cant stai
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Case studies 121 6.9a Smooth surfac
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Case studies 123 slice editing of t
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Case studies 125 6.12 Removal of bo
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Case studies 127 18. Williams R J,
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Case studies 129 and passing throug
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Case studies 131 6.14 The effect of
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Case studies 133 6.18 The block ove
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Case studies 135 create template (3
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6.4.3 Materials and methods Case st
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6.22 Resected bone compared to SLA
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Case studies 141 9. Robinson R P, C
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Case studies 143 multi-plane reform
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Case studies 145 6.25 The custom ti
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Case studies 147 6.28 Plain radiogr
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Case studies 149 reproduction of ex
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Case studies 151 manner. The softwa
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Case studies 153 surface on which t
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6.33 The guide being fi tted to the
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Case studies 157 The more fundament
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Case studies 159 25. Sarment D P, A
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6.37 Stereolithography models. 6.38
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Case studies 163 6.41 Merged pre- a
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REHABILITATION APPLICATIONS 6.8 Reh
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6.8.3 Methods Preliminary trial of
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Case studies 169 prototyping system
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Case studies 171 The aperture for t
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Case studies 173 7. Manners C R (19
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Case studies 175 during the acquisi
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6.46 Smoothing the data (exaggerate
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6.49 Plaster fi lled SL mould. Case
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Case studies 181 diffi cult for hos
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Case studies 183 extremely diffi cu
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Case studies 185 back as shown in F
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6.54 The result of the Boolean subt
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6.56 The SLA model of the plate. Ca
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6.59 SLA implant on SLA model of de
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Case studies 193 In the near future
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Case studies 195 anatomical forms a
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Case studies 197 Establishing the c
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Case studies 199 6.63 The rough (a)
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Case studies 201 The fi nal prosthe
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Case studies 203 grating the techno
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Case studies 205 6.12 Rehabilitatio
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Case studies 207 • Data capture N
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Case studies 209 placement of two i
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Case studies 211 technique that has
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Case studies 213 6.72 The bar locat
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Case studies 215 Stereolithography
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Case studies 217 authors intend to
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Case studies 219 17. Kau C H, Zhuro
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Case studies 221 310, Sainte-Foy, Q
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6.77a The physically surveyed cast.
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Creation of relief Case studies 225
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6.81 Construction curves. Case stud
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6.83 The support structure in 3D Li
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Finishing Case studies 231 The cast
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Case studies 233 6.14 Rehabilitatio
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6.86 The RPD framework designed in
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Second experiment Case studies 237
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Case studies 239 6.90 Close up view
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Table 6.2 Process steps and associa
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Case studies 243 9. Budtz-Jorgensen
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Case studies 245 micro-computed tom
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Case studies 247 supports became av
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Case studies 249 However, the probl
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6.96 Model of one of the samples su
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6.15.9 Reference Case studies 253 1
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Case studies 255 mummies. Mimics so
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Case studies 257 6.101 3D reconstru
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Case studies 259 6.103 The stages o
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6.16.5 Conclusions Case studies 261
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Case studies 263 the patient’s de
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Case studies 265 and sharp radii re
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Suitable technologies identifi ed C
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Case studies 269 6.107 A close-up p
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6.110 The selected region of facial
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Case studies 273 patterns were buil
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Case studies 275 7. Cheah C M, Chua
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Future developments 277 slices to b
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Future developments 279 ments that
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Glossary and explanatory notes 281
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Glossary and explanatory notes 283
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Further reading on anatomy Last’s
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Fundamentals of Facial Prosthetics
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Rapid Prototyping and Tooling Resea
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Contacts 3D Systems 26081 Avenue Ha
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Marcam Engineering GmbH Fahrenheits
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3D Lightyear TM 229, 247, 249-51, 2
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Removable Partial Denture 219-20, 2
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4.10 A three-dimensional shaded ima
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6.41 Merged pre- and post-operative
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