TY - GEN
T1 - GPU-Accelerated Enhanced Marching Cubes 33 for Fast 3D Reconstruction of Large Bone Defect CT Images
AU - Chin, Daniel Jie Yuan
AU - Mohamed, Ahmad Sufril Azlan
AU - Shariff, Khairul Anuar
AU - Ishikawa, Kunio
N1 - Funding Information:
Acknowledgement. The authors are grateful to Universiti Sains Malaysia and ASEAN University Network/Southeast Asia Engineering Education Development Network (AUN/SEED-Net) Japan International Cooperation Agency (JICA) project for supporting this documented work through Special Program for Research Against COVID-19 (SPRAC) grant [304/PBA-HAN/6050449/A119].
Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - With the advancement in three-dimensional technologies, three-dimensional reconstruction of medical images serves as reliable assistance for doctors and surgeons in evaluating and diagnosing bone defects. Amongst the existing reconstruction methods, the Marching Cubes algorithm is highly popular in the surface rendering research study. There are many improvements made over the Marching Cubes algorithm, but due to the relatively small image datasets used during evaluation, it is difficult to judge the effectiveness of the improvements on large image datasets and the reconstructed models may not be viewable in lower-end specs digital devices like tablets and smartphones. Thus, an enhancement over the extended Marching Cubes 33 with graphics processing unit acceleration to improve the reconstruction accuracy, execution time, and model portability for large image datasets is proposed in this study. The obtained results show that the proposed enhancement successfully increased the accuracy by 5.29%, decreased the execution time by 11.16%, and decreased the number of vertices and faces by 73.72%. This shows that it is possible to view bone defect models with a high similarity percentage on lower-end spec digital devices and print them out with a three-dimensional printer.
AB - With the advancement in three-dimensional technologies, three-dimensional reconstruction of medical images serves as reliable assistance for doctors and surgeons in evaluating and diagnosing bone defects. Amongst the existing reconstruction methods, the Marching Cubes algorithm is highly popular in the surface rendering research study. There are many improvements made over the Marching Cubes algorithm, but due to the relatively small image datasets used during evaluation, it is difficult to judge the effectiveness of the improvements on large image datasets and the reconstructed models may not be viewable in lower-end specs digital devices like tablets and smartphones. Thus, an enhancement over the extended Marching Cubes 33 with graphics processing unit acceleration to improve the reconstruction accuracy, execution time, and model portability for large image datasets is proposed in this study. The obtained results show that the proposed enhancement successfully increased the accuracy by 5.29%, decreased the execution time by 11.16%, and decreased the number of vertices and faces by 73.72%. This shows that it is possible to view bone defect models with a high similarity percentage on lower-end spec digital devices and print them out with a three-dimensional printer.
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U2 - 10.1007/978-3-030-90235-3_33
DO - 10.1007/978-3-030-90235-3_33
M3 - Conference contribution
AN - SCOPUS:85120534381
SN - 9783030902346
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 374
EP - 384
BT - Advances in Visual Informatics - 7th International Visual Informatics Conference, IVIC 2021, Proceedings
A2 - Badioze Zaman, Halimah
A2 - Smeaton, Alan F.
A2 - Shih, Timothy K.
A2 - Velastin, Sergio
A2 - Terutoshi, Tada
A2 - Jørgensen, Bo Nørregaard
A2 - Aris, Hazleen
A2 - Ibrahim, Nazrita
PB - Springer Science and Business Media Deutschland GmbH
T2 - 7th International Conference on Advances in Visual Informatics, IVIC 2021
Y2 - 23 November 2021 through 25 November 2021
ER -