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油岩心 CT 图像三维裂缝分割研究。

Research on 3D crack segmentation of CT images of oil rock core.

机构信息

Key Laboratory of Optoelectronic Technology and System of the Education Ministry, Chongqing University, Chongqing, China.

Engineering Research Center of Industrial Computed Tomography Nondestructive Testing of the Education Ministry, Chongqing University, Chongqing, China.

出版信息

PLoS One. 2021 Oct 14;16(10):e0258463. doi: 10.1371/journal.pone.0258463. eCollection 2021.

DOI:10.1371/journal.pone.0258463
PMID:34648545
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8516274/
Abstract

In this paper, we propose a framework for CT image segmentation of oil rock core. According to the characteristics of CT image of oil rock core, the existing level set segmentation algorithm is improved. Firstly, an algorithm of Chan-Vese (C-V) model is carried out to segment rock core from image background. Secondly the gray level of image background region is replaced by the average gray level of rock core, so that image background does not affect the binary segmentation. Next, median filtering processing is carried out. Finally, an algorithm of local binary fitting (LBF) model is executed to obtain the crack region. The proposed algorithm has been applied to oil rock core CT images with promising results.

摘要

本文提出了一种针对油岩心 CT 图像分割的框架。根据油岩心 CT 图像的特点,对现有的水平集分割算法进行了改进。首先,进行 Chan-Vese(C-V)模型算法,将岩心从图像背景中分割出来。其次,用岩心的平均灰度值替换图像背景区域的灰度值,使图像背景不影响二值分割。接下来,进行中值滤波处理。最后,执行局部二值拟合(LBF)模型算法,得到裂缝区域。所提出的算法已应用于油岩心 CT 图像,取得了良好的效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa82/8516274/09975f28fd87/pone.0258463.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa82/8516274/7a5392f0d38c/pone.0258463.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa82/8516274/124d2f9fedb8/pone.0258463.g002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa82/8516274/650a073a892e/pone.0258463.g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa82/8516274/89b69eac2e61/pone.0258463.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa82/8516274/c3271140f704/pone.0258463.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa82/8516274/09975f28fd87/pone.0258463.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa82/8516274/7a5392f0d38c/pone.0258463.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa82/8516274/124d2f9fedb8/pone.0258463.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa82/8516274/62d2575a51ae/pone.0258463.g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa82/8516274/89b69eac2e61/pone.0258463.g006.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa82/8516274/09975f28fd87/pone.0258463.g008.jpg

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2
Distance regularized two level sets for segmentation of left and right ventricles from cine-MRI.用于从心脏磁共振电影成像中分割左、右心室的距离正则化双水平集
Magn Reson Imaging. 2016 Jun;34(5):699-706. doi: 10.1016/j.mri.2015.12.027. Epub 2015 Dec 29.
3
A novel method for 3D crack edge extraction in CT volume data.
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4
A level set method for image segmentation in the presence of intensity inhomogeneities with application to MRI.基于水平集的 MRI 图像强度不均匀性校正分割方法
IEEE Trans Image Process. 2011 Jul;20(7):2007-16. doi: 10.1109/TIP.2011.2146190. Epub 2011 Apr 21.
5
Minimization of region-scalable fitting energy for image segmentation.用于图像分割的区域可缩放拟合能量最小化
IEEE Trans Image Process. 2008 Oct;17(10):1940-9. doi: 10.1109/TIP.2008.2002304.