Development of Mesh-Defect Removal Algorithm to Enhance the Fitting of 3D-Printed Parts for Comminuted Bone Fractures

PurposeMesh self-intersection defects and image noise may prevent 3D model reconstruction and mesh formation of bones with comminuted fractures, making it impossible to assemble 3D-printed fragments perfectly. This study proposes an algorithm to remove overlapping meshes and to smooth fracture surfaces in order to fabricate well-assembled 3D-printed bone.Methods3D bone reconstruction, segmentation, and reduction were directly performed for three different classes of clinical fracture cases: pelvic 62-B1, 62-C2, and femur 31-A2.2. In contrast to the current Boolean operation, the proposed algorithm is not only capable of detecting overlapping meshes, but also recognizing the contact regions and detecting the boundary of each contact region. Hence, it was implemented in order to remove overlapping meshes and ensure that fragments fit together when physically assembled. Both gap distance and overlapping mesh errors during assembly of the 3D model from printed bone fragments were calculated and analyzed.Results and ConclusionsBased on the comparison of results between the bone model before and after removing mesh defects, the RMS error is less than 0.33 mm and gap error is 3 mm, indicating that the proposed technique has high potential for eliminating mesh defects and providing a 3D-printed bone fracture model that is easy to assemble and disassemble.

[1]  Anton du Plessis,et al.  X-Ray Microcomputed Tomography in Additive Manufacturing: A Review of the Current Technology and Applications , 2018, 3D Printing and Additive Manufacturing.

[2]  Roberto Scopigno,et al.  In Memoriam , 2017 .

[3]  Pengcheng Liu,et al.  A computational/experimental platform for investigating three-dimensional puzzle solving of comminuted articular fractures , 2011, Computer methods in biomechanics and biomedical engineering.

[4]  Marc Alexa,et al.  Laplacian mesh optimization , 2006, GRAPHITE '06.

[5]  Rosaire Mongrain,et al.  3D printing materials and their use in medical education: a review of current technology and trends for the future , 2017, BMJ Simulation & Technology Enhanced Learning.

[6]  A. Mosnier,et al.  Patient safety incidents are common in primary care: A national prospective active incident reporting survey , 2017, PloS one.

[7]  Frank Langlotz,et al.  Evaluating partial surface matching for fracture reduction assessment , 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

[8]  Tim Weyrich,et al.  Learning how to match fresco fragments , 2011, JOCCH.

[9]  W. Murphy,et al.  AO principles of fracture management , 2018, Acta chirurgica Belgica.

[10]  Andreas A. Giannopoulos,et al.  Post-processing of DICOM Images , 2017 .

[11]  Nabil Zemiti,et al.  Geometric and mechanical evaluation of 3D-printing materials for skull base anatomical education and endoscopic surgery simulation – A first step to create reliable customized simulators , 2017, PloS one.

[12]  Tatiana Kelil,et al.  3D printing from MRI Data: Harnessing strengths and minimizing weaknesses , 2017, Journal of magnetic resonance imaging : JMRI.

[13]  Jiing-Yih Lai,et al.  Algorithm for segmentation and reduction of fractured bones in computer-aided preoperative surgery , 2016, ICBBE '16.

[14]  Yen-Wei Chen,et al.  Computer-Assisted Preoperative Planning for Reduction of Proximal Femoral Fracture Using 3-D-CT Data , 2009, IEEE Transactions on Biomedical Engineering.

[15]  F. Rybicki,et al.  Medical 3D Printing for the Radiologist. , 2015, Radiographics : a review publication of the Radiological Society of North America, Inc.

[16]  J. Tonetti,et al.  Computer assisted surgery in preoperative planning of acetabular fracture surgery: state of the art , 2018, Expert review of medical devices.

[17]  Zoltan Kato,et al.  Realigning 2D and 3D Object Fragments without Correspondences , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  Jiing-Yih Lai,et al.  Integration of computer-aided pre-operative planning and 3D printing technology for comminuted fracture bone surgery , 2017, 2017 International Conference on Applied System Innovation (ICASI).

[19]  Ramin Javan,et al.  Understanding Spatially Complex Segmental and Branch Anatomy Using 3D Printing: Liver, Lung, Prostate, Coronary Arteries, and Circle of Willis. , 2016, Academic radiology.

[20]  Simon Winkelbach,et al.  Pairwise Matching of 3D Fragments Using Cluster Trees , 2008, International Journal of Computer Vision.

[21]  Ismail Hakki Toroslu,et al.  Automatic reconstruction of broken 3-D surface objects , 1999, Comput. Graph..

[22]  Gary Tse,et al.  The role of 3D printing in anatomy education and surgical training: A narrative review , 2017 .

[23]  Gábor Székely,et al.  Computer assisted reconstruction of complex proximal humerus fractures for preoperative planning , 2012, Medical Image Anal..

[24]  Kang Zhang,et al.  3D Fragment Reassembly Using Integrated Template Guidance and Fracture-Region Matching , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[25]  Sylvain Lefebvre,et al.  From 3D models to 3D prints: an overview of the processing pipeline , 2017, Comput. Graph. Forum.

[26]  Cristian A. Linte,et al.  3D printing for orthopedic applications: from high resolution cone beam CT images to life size physical models , 2017, Medical Imaging.

[27]  K. S. Arun,et al.  Least-Squares Fitting of Two 3-D Point Sets , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[28]  Maikel Beerens,et al.  Orbital Wall Reconstruction with Two-Piece Puzzle 3D Printed Implants: Technical Note , 2016, Craniomaxillofacial trauma & reconstruction.

[29]  Jiing-Yih Lai,et al.  Localization of parts with irregular shape for CMM inspection , 2007 .

[30]  Georgios Papaioannou,et al.  From Reassembly to Object Completion: A Complete Systems Pipeline , 2017, JOCCH.

[31]  Mark Michalski,et al.  3D printing from diagnostic images: a radiologist’s primer with an emphasis on musculoskeletal imaging—putting the 3D printing of pathology into the hands of every physician , 2016, Skeletal Radiology.

[32]  Nicola Bizzotto,et al.  Three-Dimensional Printing of Bone Fractures , 2015, Surgical innovation.

[33]  Vinay Mohan Das,et al.  Digital reconstruction of pavilions described in an ancient Indian architectural treatise , 2011, JOCCH.

[34]  Marco Attene,et al.  A lightweight approach to repairing digitized polygon meshes , 2010, The Visual Computer.

[35]  Günther Greiner,et al.  Interactive Repositioning of Bone Fracture Segments , 2001, VMV.

[36]  Jiing-Yih Lai,et al.  Computer-assisted Fracture Reduction and Fixation Simulation for Pelvic Fractures , 2014 .

[37]  Jiing-Yih Lai,et al.  Detecting and removing overlap meshes for the assembly of 3D-printed fractured bones , 2018, 2018 IEEE International Conference on Applied System Invention (ICASI).

[38]  Nicola Bizzotto,et al.  3D Printed replica of articular fractures for surgical planning and patient consent: a two years multi-centric experience , 2016, 3D Printing in Medicine.