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Volume 9, Issue 4
Hippocampus Segmentation via active contour model

Shangbing Gao and Haiyan Zhou and Yuebin Lin and Yue Zhang

J. Info. Comput. Sci. , 9 (2014), pp. 262-266.

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  • Abstract
Since hippocampal volume measurement is often used in studying Alzheimer’s disease to assess disease progression, automatic hippocampus segmentation is an important task in clinical applications. However, it is a challenging task due to its small size, complex shape, fuzzy boundaries, partial volume effects, and anatomical variability. In this paper we propose a new segmentation method to segment the hippocampus from brain MRI images automatically.This proposed method presents a new region-based signed pressure force function, which can efficiently stop the contours at weak boundary. Experimental results show that the model can fast and effectively segment the intensity inhomogeneous images.
  • Keywords

hippocampus Image segmentation active contour Chan-Vese.

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COPYRIGHT: © Global Science Press

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@Article{JICS-9-262, author = {Shangbing Gao and Haiyan Zhou and Yuebin Lin and Yue Zhang}, title = {Hippocampus Segmentation via active contour model}, journal = {Journal of Information and Computing Science}, year = {2024}, volume = {9}, number = {4}, pages = {262--266}, abstract = {Since hippocampal volume measurement is often used in studying Alzheimer’s disease to assess disease progression, automatic hippocampus segmentation is an important task in clinical applications. However, it is a challenging task due to its small size, complex shape, fuzzy boundaries, partial volume effects, and anatomical variability. In this paper we propose a new segmentation method to segment the hippocampus from brain MRI images automatically.This proposed method presents a new region-based signed pressure force function, which can efficiently stop the contours at weak boundary. Experimental results show that the model can fast and effectively segment the intensity inhomogeneous images. }, issn = {1746-7659}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22569.html} }
TY - JOUR T1 - Hippocampus Segmentation via active contour model AU - Shangbing Gao and Haiyan Zhou and Yuebin Lin and Yue Zhang JO - Journal of Information and Computing Science VL - 4 SP - 262 EP - 266 PY - 2024 DA - 2024/01 SN - 9 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22569.html KW - hippocampus KW - Image segmentation KW - active contour KW - Chan-Vese. AB - Since hippocampal volume measurement is often used in studying Alzheimer’s disease to assess disease progression, automatic hippocampus segmentation is an important task in clinical applications. However, it is a challenging task due to its small size, complex shape, fuzzy boundaries, partial volume effects, and anatomical variability. In this paper we propose a new segmentation method to segment the hippocampus from brain MRI images automatically.This proposed method presents a new region-based signed pressure force function, which can efficiently stop the contours at weak boundary. Experimental results show that the model can fast and effectively segment the intensity inhomogeneous images.
Shangbing Gao and Haiyan Zhou and Yuebin Lin and Yue Zhang. (2024). Hippocampus Segmentation via active contour model. Journal of Information and Computing Science. 9 (4). 262-266. doi:
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