Automatic Segmentation of Hepatic Tissue and 3D Volume Analysis of Cirrhosis in Multi-Detector Row CT Scans and MR Imaging

Xuejun ZHANG; Wenguang LI; Hiroshi FUJITA; Masayuki KANEMATSU; Takeshi HARA; Xiangrong ZHOU; Hiroshi KONDO; Hiroaki HOSHI

Automatic Segmentation of Hepatic Tissue and 3D Volume Analysis of Cirrhosis in Multi-Detector Row CT Scans and MR Imaging

Xuejun ZHANG, Wenguang LI, Hiroshi FUJITA, Masayuki KANEMATSU, Takeshi HARA, Xiangrong ZHOU, Hiroshi KONDO, Hiroaki HOSHI

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The enlargement of the left lobe of the liver and the shrinkage of the right lobe are helpful signs at MR imaging in diagnosis of cirrhosis of the liver. To investigate whether the volume ratio of left-to-whole (LTW) is effective to differentiate cirrhosis from a normal liver, we developed an automatic algorithm for three-dimensional (3D) segmentation and volume calculation of the liver region in multi-detector row CT scans and MR imaging. From one manually selected slice that contains a large liver area, two edge operators are applied to obtain the initial liver area, from which the mean gray value is calculated as threshold value in order to eliminate the connected organs or tissues. The final contour is re-confirmed by using thresholding technique. The liver region in the next slice is generated by referring to the result from the last slice. After continuous procedure of this segmentation on each slice, the 3D liver is reconstructed from all the extracted slices and the surface image can be displayed from different view points by using the volume rendering technique. The liver is then separated into the left and the right lobe by drawing an inter-segmental plane manually, and the volume in each part is calculated slice by slice. The degree of cirrhosis can be defined as the ratio of volume in these two lobes. Four cases including normal and cirrhotic liver with MR and CT slices are used for 3D segmentation and visualization. The volume ratio of LTW was relatively higher in cirrhosis than in the normal cases in both MR and CT cases. The average error rate on liver segmentation was within 5.6% after employing in 30 MR cases. These results demonstrate that the performance in our 3D segmentation was satisfied and the LTW ratio may be effective to differentiate cirrhosis.

Publication: IEICE TRANSACTIONS on Information Vol.E87-D No.8 pp.2138-2147

Publication Date: 2004/08/01

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Type of Manuscript: PAPER

Category: Biological Engineering

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Xuejun ZHANG, Wenguang LI, Hiroshi FUJITA, Masayuki KANEMATSU, Takeshi HARA, Xiangrong ZHOU, Hiroshi KONDO, Hiroaki HOSHI, "Automatic Segmentation of Hepatic Tissue and 3D Volume Analysis of Cirrhosis in Multi-Detector Row CT Scans and MR Imaging" in IEICE TRANSACTIONS on Information, vol. E87-D, no. 8, pp. 2138-2147, August 2004, doi: .
Abstract: The enlargement of the left lobe of the liver and the shrinkage of the right lobe are helpful signs at MR imaging in diagnosis of cirrhosis of the liver. To investigate whether the volume ratio of left-to-whole (LTW) is effective to differentiate cirrhosis from a normal liver, we developed an automatic algorithm for three-dimensional (3D) segmentation and volume calculation of the liver region in multi-detector row CT scans and MR imaging. From one manually selected slice that contains a large liver area, two edge operators are applied to obtain the initial liver area, from which the mean gray value is calculated as threshold value in order to eliminate the connected organs or tissues. The final contour is re-confirmed by using thresholding technique. The liver region in the next slice is generated by referring to the result from the last slice. After continuous procedure of this segmentation on each slice, the 3D liver is reconstructed from all the extracted slices and the surface image can be displayed from different view points by using the volume rendering technique. The liver is then separated into the left and the right lobe by drawing an inter-segmental plane manually, and the volume in each part is calculated slice by slice. The degree of cirrhosis can be defined as the ratio of volume in these two lobes. Four cases including normal and cirrhotic liver with MR and CT slices are used for 3D segmentation and visualization. The volume ratio of LTW was relatively higher in cirrhosis than in the normal cases in both MR and CT cases. The average error rate on liver segmentation was within 5.6% after employing in 30 MR cases. These results demonstrate that the performance in our 3D segmentation was satisfied and the LTW ratio may be effective to differentiate cirrhosis.
URL: https://global.ieice.org/en_transactions/information/10.1587/e87-d_8_2138/_p

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@ARTICLE{e87-d_8_2138,
author={Xuejun ZHANG, Wenguang LI, Hiroshi FUJITA, Masayuki KANEMATSU, Takeshi HARA, Xiangrong ZHOU, Hiroshi KONDO, Hiroaki HOSHI, },
journal={IEICE TRANSACTIONS on Information},
title={Automatic Segmentation of Hepatic Tissue and 3D Volume Analysis of Cirrhosis in Multi-Detector Row CT Scans and MR Imaging},
year={2004},
volume={E87-D},
number={8},
pages={2138-2147},
abstract={The enlargement of the left lobe of the liver and the shrinkage of the right lobe are helpful signs at MR imaging in diagnosis of cirrhosis of the liver. To investigate whether the volume ratio of left-to-whole (LTW) is effective to differentiate cirrhosis from a normal liver, we developed an automatic algorithm for three-dimensional (3D) segmentation and volume calculation of the liver region in multi-detector row CT scans and MR imaging. From one manually selected slice that contains a large liver area, two edge operators are applied to obtain the initial liver area, from which the mean gray value is calculated as threshold value in order to eliminate the connected organs or tissues. The final contour is re-confirmed by using thresholding technique. The liver region in the next slice is generated by referring to the result from the last slice. After continuous procedure of this segmentation on each slice, the 3D liver is reconstructed from all the extracted slices and the surface image can be displayed from different view points by using the volume rendering technique. The liver is then separated into the left and the right lobe by drawing an inter-segmental plane manually, and the volume in each part is calculated slice by slice. The degree of cirrhosis can be defined as the ratio of volume in these two lobes. Four cases including normal and cirrhotic liver with MR and CT slices are used for 3D segmentation and visualization. The volume ratio of LTW was relatively higher in cirrhosis than in the normal cases in both MR and CT cases. The average error rate on liver segmentation was within 5.6% after employing in 30 MR cases. These results demonstrate that the performance in our 3D segmentation was satisfied and the LTW ratio may be effective to differentiate cirrhosis.},
keywords={},
doi={},
ISSN={},
month={August},}

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TY - JOUR
TI - Automatic Segmentation of Hepatic Tissue and 3D Volume Analysis of Cirrhosis in Multi-Detector Row CT Scans and MR Imaging
T2 - IEICE TRANSACTIONS on Information
SP - 2138
EP - 2147
AU - Xuejun ZHANG
AU - Wenguang LI
AU - Hiroshi FUJITA
AU - Masayuki KANEMATSU
AU - Takeshi HARA
AU - Xiangrong ZHOU
AU - Hiroshi KONDO
AU - Hiroaki HOSHI
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E87-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2004
AB - The enlargement of the left lobe of the liver and the shrinkage of the right lobe are helpful signs at MR imaging in diagnosis of cirrhosis of the liver. To investigate whether the volume ratio of left-to-whole (LTW) is effective to differentiate cirrhosis from a normal liver, we developed an automatic algorithm for three-dimensional (3D) segmentation and volume calculation of the liver region in multi-detector row CT scans and MR imaging. From one manually selected slice that contains a large liver area, two edge operators are applied to obtain the initial liver area, from which the mean gray value is calculated as threshold value in order to eliminate the connected organs or tissues. The final contour is re-confirmed by using thresholding technique. The liver region in the next slice is generated by referring to the result from the last slice. After continuous procedure of this segmentation on each slice, the 3D liver is reconstructed from all the extracted slices and the surface image can be displayed from different view points by using the volume rendering technique. The liver is then separated into the left and the right lobe by drawing an inter-segmental plane manually, and the volume in each part is calculated slice by slice. The degree of cirrhosis can be defined as the ratio of volume in these two lobes. Four cases including normal and cirrhotic liver with MR and CT slices are used for 3D segmentation and visualization. The volume ratio of LTW was relatively higher in cirrhosis than in the normal cases in both MR and CT cases. The average error rate on liver segmentation was within 5.6% after employing in 30 MR cases. These results demonstrate that the performance in our 3D segmentation was satisfied and the LTW ratio may be effective to differentiate cirrhosis.
ER -