Deep Geodesic Learning for Segmentation and Anatomical Landmarking

作者: Neslisah Torosdagli , Denise K. Liberton , Payal Verma , Murat Sincan , Janice S. Lee

DOI: 10.1109/TMI.2018.2875814

关键词:

摘要: In this paper, we propose a novel deep learning framework for anatomy segmentation and automatic landmarking. Specifically, focus on the challenging problem of mandible from cone-beam computed tomography (CBCT) scans identification 9 anatomical landmarks geodesic space. The overall approach employs three inter-related steps. first step, neural network architecture with carefully designed regularization, hyper-parameters to perform image without need data augmentation complex post-processing refinement. second formulate landmark localization directly space sparsely-spaced landmarks. third utilize long short-term memory identify closely-spaced landmarks, which is rather difficult obtain using other standard networks. proposed fully automated method showed superior efficacy compared state-of-the-art landmarking approaches in craniofacial anomalies diseased states. We used very CBCT set 50 patients high-degree craniomaxillofacial variability that realistic clinical practice. qualitative visual inspection was conducted distinct 250 high variability. have also shown performance an independent MICCAI Head-Neck Challenge (2015).

参考文章(28)
Manasi Datar, Ilwoo Lyu, SunHyung Kim, Joshua Cates, Martin A. Styner, Ross Whitaker, Geodesic Distances to Landmarks for Dense Correspondence on Ensembles of Complex Shapes medical image computing and computer assisted intervention. ,vol. 16, pp. 19- 26 ,(2013) , 10.1007/978-3-642-40763-5_3
Stefanie Wuhrer, Prosenjit Bose, Anil Maheshwari, Chang Shu, A survey of geodesic paths on 3D surfaces Computational Geometry: Theory and Applications. ,vol. 44, pp. 486- 498 ,(2011) , 10.1016/J.COMGEO.2011.05.006
Philipp Fischer, Thomas Brox, None, U-Net: Convolutional Networks for Biomedical Image Segmentation medical image computing and computer assisted intervention. pp. 234- 241 ,(2015) , 10.1007/978-3-319-24574-4_28
Abhishek Gupta, Om Prakash Kharbanda, Viren Sardana, Rajiv Balachandran, Harish Kumar Sardana, A knowledge-based algorithm for automatic detection of cephalometric landmarks on CBCT images computer assisted radiology and surgery. ,vol. 10, pp. 1737- 1752 ,(2015) , 10.1007/S11548-015-1173-6
Shoaleh Shahidi, Ehsan Bahrampour, Elham Soltanimehr, Ali Zamani, Morteza Oshagh, Marzieh Moattari, Alireza Mehdizadeh, The accuracy of a designed software for automated localization of craniofacial landmarks on CBCT images BMC Medical Imaging. ,vol. 14, pp. 32- 32 ,(2014) , 10.1186/1471-2342-14-32
James J. Xia, Jaime Gateno, John F. Teichgraeber, New Clinical Protocol to Evaluate Craniomaxillofacial Deformity and Plan Surgical Correction Journal of Oral and Maxillofacial Surgery. ,vol. 67, pp. 2093- 2106 ,(2009) , 10.1016/J.JOMS.2009.04.057
Ricardo Fabbri, Luciano Da F. Costa, Julio C. Torelli, Odemir M. Bruno, 2D Euclidean distance transform algorithms ACM Computing Surveys. ,vol. 40, pp. 1- 44 ,(2008) , 10.1145/1322432.1322434
Sepp Hochreiter, Jürgen Schmidhuber, Long short-term memory Neural Computation. ,vol. 9, pp. 1735- 1780 ,(1997) , 10.1162/NECO.1997.9.8.1735
H. Breu, J. Gil, D. Kirkpatrick, M. Werman, Linear time Euclidean distance transform algorithms IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 17, pp. 529- 533 ,(1995) , 10.1109/34.391389
K. Kian Ang, Qiang Zhang, David I. Rosenthal, Phuc Felix Nguyen-Tan, Eric J. Sherman, Randal S. Weber, James M. Galvin, James A. Bonner, Jonathan Harris, Adel K. El-Naggar, Maura L. Gillison, Richard C. Jordan, Andre A. Konski, Wade L. Thorstad, Andy Trotti, Jonathan J. Beitler, Adam S. Garden, William J. Spanos, Sue S. Yom, Rita S. Axelrod, Randomized Phase III Trial of Concurrent Accelerated Radiation Plus Cisplatin With or Without Cetuximab for Stage III to IV Head and Neck Carcinoma: RTOG 0522 Journal of Clinical Oncology. ,vol. 32, pp. 2940- 2950 ,(2014) , 10.1200/JCO.2013.53.5633