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Automatic Vertebra Labeling in Large-Scale 3D CT Using Deep Image-to-Image Network with Message Passing and Sparsity Regularization [chapter]

Dong Yang, Tao Xiong, Daguang Xu, Qiangui Huang, David Liu, S. Kevin Zhou, Zhoubing Xu, JinHyeong Park, Mingqing Chen, Trac D. Tran, Sang Peter Chin, Dimitris Metaxas (+1 others)
2017 Lecture Notes in Computer Science  
In this paper, we propose an automatic and fast algorithm to localize and label the vertebra centroids in 3D CT volumes.  ...  First, we deploy a deep image-to-image network (DI2IN) to initialize vertebra locations, employing the convolutional encoder-decoder architecture together with multi-level feature concatenation and deep  ...  Conclusion In this paper, we proposed an effective and fast automatic method to localize and label vertebra centroids in 3D CT volumes.  ... 
doi:10.1007/978-3-319-59050-9_50 fatcat:smwgu634ebembiagsmahq5bgvi

Residual Block-based Multi-Label Classification and Localization Network with Integral Regression for Vertebrae Labeling [article]

Chunli Qin, Demin Yao, Han Zhuang, Hui Wang, Yonghong Shi, Zhijian Song
2020 arXiv   pre-print
Therefore, for end-to-end differential training of vertebra coordinates on CT scans, a robust and accurate automatic vertebral labeling algorithm is proposed in this study.  ...  Accurate identification and localization of the vertebrae in CT scans is a critical and standard preprocessing step for clinical spinal diagnosis and treatment.  ...  ACKNOWLEDGMENT This research was supported by grants from the National Key Research and Development Program of China (2017YFC0110701).  ... 
arXiv:2001.00170v1 fatcat:zx5kkjghznh7loqjsp6tzgagh4

A survey on deep learning in medical image analysis

Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen A.W.M. van der Laak, Bram van Ginneken, Clara I. Sánchez
2017 Medical Image Analysis  
This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year.  ...  Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images.  ...  Papers not reporting results on medical image data or only using standard feed-forward neural networks with handcrafted features were excluded.  ... 
doi:10.1016/ pmid:28778026 fatcat:esbj72ftwvbgzh6jgw367k73j4

Closing the Gap between Deep and Conventional Image Registration using Probabilistic Dense Displacement Networks [article]

Mattias P. Heinrich
2019 arXiv   pre-print
When labelled scans are scarce and anatomical differences large, conventional registration has often remained superior to deep learning methods that have so far mainly dealt with relatively small or low-complexity  ...  Nonlinear image registration continues to be a fundamentally important tool in medical image analysis.  ...  (over dim. 4-6) is used in a non-local label loss and converted to 3D displacements for a diffusion regularisation and to warp images. also introduce a new non-local label loss for improved guidance instead  ... 
arXiv:1907.10931v1 fatcat:bfnkraguo5erzpne4dfvgoh6ku

Neural Networks Regularization Through Representation Learning [article]

Soufiane Belharbi
2018 arXiv   pre-print
In this application, the task consists in localizing the third lumbar vertebra in a 3D CT scan.  ...  Neural network models and deep models are one of the leading and state of the art models in machine learning.  ...  I would like also to thank my advisors Clément Chatelain and Romain Hérault for all their advice and knowledge they have shared with me.  ... 
arXiv:1807.05292v1 fatcat:qwqvdyzkf5alrjtp6fnclxpuqu

Deformable models and machine learning for large-scale cardiac MRI image analytics

Dong Yang
Then an unsupervised learning method using deep neural networks is adopted to compute the in-plane deformation field.  ...  Our proposed approach has a great potential to be applied in the analysis of large-scale MRI datasets of various cardiovascular diseases, and used to guide the administration of CRT.  ...  Proposed deep image-to-image network (DI2IN) used in 3D CT images experiments.  ... 
doi:10.7282/t3-x9v0-9704 fatcat:ki54qb4qqvexzg5guuqqjcwgb4

Neurological and mental disorders [chapter]

Tarakad S. Ramachandran
2013 Alcohol  
She has taught Medical and Biological Sciences in various universities in Australia, USA, UAE, Bahrain, Pakistan and Brunei.  ...  During this period, she was also engaged in research by obtaining local and international grants (total of over 2.4 million USD) and translating this into products such as a rapid diagnostic test for stroke  ...  This chapter is distributed under the terms of the Creative Commons Attribution License ( by/3.0), which permits unrestricted use, distribution, and reproduction in  ... 
doi:10.1093/acprof:oso/9780199655786.003.0036 fatcat:s4tdazxlxzfnldqys522y4zqvm

Editorial Associate: Position Papers of the 2017 Federated Conference on Computer Science and Information Systems and Information Systems Cover photo

Maria Ganzha, Leszek Maciaszek, Marcin Paprzycki, Maria Ganzha, Leszek Maciaszek, Marcin Paprzycki, Wil Van Der Aalst, Frederik Ahlemann, Marco Aiello, Mohammed Atiquzzaman, Barrett Bryant, Ana Fred (+17 others)
Polskie Towarzystwo Informatyczne Annals of Computer Science and Information Systems   unpublished
ACKNOWLEDGMENT This work was supported by the Business Informatics Group at Dublin City University and in part, by Science Foundation Ireland grant 13/RC/2094 and co-funded under the European Regional  ...  Programme to Lero -the Irish Software Research Centre (  ...  In addition, several regularization terms such as weight decay and sparsity constraints are implemented.  ... 

Proceedings, MSVSCC 2017

Proceedings of the 11th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 20, 2017 at VMASC in Suffolk, Virginia.  ...  Margaret Mulvey, for helping us with the revisions on the paper, allowing us to use her room to work on the model, and coordinating our meetings with Dr. Tolk with our mentorship coordinator, Mrs.  ...  Andreas Tolk of MITRE for taking the time to give us excellent advice and guidance on war simulation. We would also like to thank Dr. Bedir and Dr.  ... 
doi:10.25776/zjc7-vp17 fatcat:ty74lwf3izapxbovjb7tazwkza