딥러닝을 이용한 뇌 자기공명영상의 정량 분석 기법

  • Published : 2017.05.20

Abstract

Keywords

References

  1. S. M. Nestor et. al., "Ventricular Enlargement as a Possible Measure of Alzheimer's Disease Progression Validated Using the Alzheimer's Disease", Neuroimaging Initiative Database Brain, vol. 131, no. 9, pp. 2443-2454, 2008.
  2. M. W. Weiner et. al., "The Alzheimer's Disease Neuroimaging Initiative: a review of papers published since its inception", Alzheimer's & Dementia, vol. 9, no. 5, pp. 111-194, 2013.
  3. V. Gulshan, et. al., "Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs", JAMA, vol. 316, no. 22, pp.2402-2410, 2016. https://doi.org/10.1001/jama.2016.17216
  4. A. Esteva et. al., "Dermatologist-level Classification of Skin Cancer with Deep Neural Networks", Nature, vol. 542, no. 7639, pp.115-118, 2017. https://doi.org/10.1038/nature21056
  5. A. S. U. Pai, et. al., "Characterization of Errors in Deep Learning-based Brain MRI Segmentation", In Deep Learning for Medical Image Analysis, 2017.
  6. A. de Brebisson, et. al., "Deep Neural Networks for Anatomical Brain Segmentation", In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 20-28, 2015.
  7. Y. LeCun, et. al., "Gradient-based Learning Applied to Document Recognition", Proceedings of the IEEE, vol. 86, no. 11, pp. 2278-2324, 1998. https://doi.org/10.1109/5.726791
  8. M. Everingham, et. al., "The Pascal Visual Object Classes (VOC) Challenge", International Journal of Computer Vision, Vol. 88, no. 2, pp. 303-338, February, 2010. https://doi.org/10.1007/s11263-009-0275-4
  9. M. Havaei, et. al., "Brain Tumor Segmentation with Deep Neural Networks", Medical Image Analysis, no. 35, pp. 18-31, 2017.
  10. J. Zhao, et. al., "Stacked What-Where Auto-encoders", In Proceedings of lnternational Conference on Learning Representation (ICLR), 2016.
  11. H. Zhu, et. al., "Beyond Pixels: A Comprehensive Survey from Bottom-up to Semantic Image Segmentation and Cosegmentation", arXiv:1502.00717, 2015.
  12. J. Long, et. al., "Fully Convolutional Models for Semantic Segmentation", arXiv:1411.4038, 2014.
  13. H. Noh, et. al., "Learning Deconvolution Network for Semantic Segmentation", ICCV, 2015.
  14. L-C. Chen, et. al., "Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs", arXiv:1412.7062, 2014
  15. P. Luc, et. al., "Semantic Segmentation using Adversarial Networks", arXiv:1611.08408, 2016