Hippocampus Segmentation Techniques: A Survey

Abstract:

Since the volume of hippocampal formation has been found to be an early biomarker for MCI and Alzheimer's disease, hippocampus segmentation plays a significant role in clinical diagnosis. Because hippocampus in MR images presents features of low contrast, low signal-to-noise ratio and discontinuous boundaries, accurate segmentation still remains a challenging task. We presented a survey of the methods used to segment the hippocampal formation in MR images of human brain and concluded with a discussion on the trend of the future research in hippocampus segmentation.

• Periodical: Advanced Materials Research (Volumes 760-762)
• Pages: 2086-2090
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.760-762.2086
• Online since: September 2013
• Authors: Bing Song He, Xue Ping Zhang, Yong Gang Shi
• Keywords: Hippocampal Formation, MRI, Segmentation

References

[1] John Pluta, Paul Yushkevich, Sandhitsu Das and David Wolk, In vivo Analysis of Hippocampal Subfield Atrophy in Mild Cognitive Impairment via Semi-Automatic Segmentation of T2-Weighted MRI, " Journal of Alzheimer, s Disease, vol. 31, Dec. 2012, p.85.

DOI: 10.3233/jad-2012-111931

[2] Paul A. Yushkevich, Hongzhi Wang, John Pluta, Sandhitsu R. Das, Caryne Craige, Brian B. Avants, Michael W. Weiner, Susanne Mueller, Nearly automatic segmentation of hippocampal subfields in in vivo focal T2-weighted MRI, NeuroImage, vol. 53, Dec. 2010, p.1208.

DOI: 10.1016/j.neuroimage.2010.06.040

[3] Xianglin Li, Changyuan Wang, Yueqing Li, The methods of segmenting Hippocampal formation in MR images, in Chinese, Journal of Chinese medical imaging technology, vol. 18, Dec. 2002, p.189–190.

[4] Meng Wei, Ye Derong, A New Approach to Computer aided Segmentation of Hippocampal Formation in Human Brain MR Images, in Chinese, Journal of Capital Medical University, vol. 29, Dec. 2008, p.333–335.

[5] Jong-Bae Kim, Hang-Joon Kim, Multiresolution-based watersheds for efficient image segmentation, Pattern Recognition Letters, vol. 24, Dec. 2003, p.473–488.

DOI: 10.1016/s0167-8655(02)00270-2

[6] Xiang Lu, Shuqian Luo, Segmentation of Hippocampus in MR Using Watersnakes, IEEE: International Conference on Complex Medical Engineering, Dec. 2007, p.552–555.

DOI: 10.1109/iccme.2007.4381796

[7] Cohen Laurent D., On active contour models and balloons., CVGIP: Image understanding, vol. 53, Dec. 1991, p.211–218.

DOI: 10.1016/1049-9660(91)90028-n

[8] Williams, D.J., Shah, M., A fast algorithm for active contours, Third International Conference on Computer Vision, Dec. 1990, p.592–595, doi: 10. 1109/ICCV. 1990. 139602.

DOI: 10.1109/iccv.1990.139602

[9] Chenyang Xu, Prince, J.L., Gradient vector flow: a new external force for snakes, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Dec. 1997, p.66–71.

DOI: 10.1109/cvpr.1997.609299

[10] Shuying Zhao, Dan Zhang, Xiangman Song, Wenjun Tan, Segmentation of hippocampus in MRI images based on the improved level set, Proceedings of the 2011 Fourth International Symposium on Computational Intelligence and Design(ISCID), vol. 1, pp.123-126.

DOI: 10.1109/iscid.2011.39

[11] Collins DL, Pruessner JC, Towards accurate, automatic segmentation of the hippocampus and amygdala from MRI by augmenting ANIMAL with a template library and label fusion, Neuroimage, vol. 52, Dec. 2010, p.1355–1366.

DOI: 10.1016/j.neuroimage.2010.04.193