A dynamic adaptive region growing segmentation algorithm for tumor of liver CT images

Hong Song; Yong Wang; Xiao Chuan Huang; Jia Jia Li; Chun Meng Zhang

A dynamic adaptive region growing segmentation algorithm for tumor of liver CT images

Hong Song^*, Yong Wang, Xiao Chuan Huang, Jia Jia Li, Chun Meng Zhang

^*Corresponding author for this work

School of Computer Science and Technology

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

A novel algorithm is proposed to segment the tumor region of human liver CT image. Firstly, the region of interest (ROI) is segmented using the dynamic adaptive region growing method. Then the wormhole of the ROI is filled by morphological filtering to get the tumor region. Groups of CT images are used to test the efficiency of our algorithm. The experiments show that the algorithm is very useful for segmenting the tumor region of liver CT images. It is extremely important for calculating tumor volume and clinical treatment of the liver tumor.

Original language	English
Pages (from-to)	72-76
Number of pages	5
Journal	Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume	34
Issue number	1
Publication status	Published - Jan 2014

Keywords

Dynamic adaptive region growing
Liver CT
Morphological filtering
Tumor segmentation

Cite this

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title = "A dynamic adaptive region growing segmentation algorithm for tumor of liver CT images",

abstract = "A novel algorithm is proposed to segment the tumor region of human liver CT image. Firstly, the region of interest (ROI) is segmented using the dynamic adaptive region growing method. Then the wormhole of the ROI is filled by morphological filtering to get the tumor region. Groups of CT images are used to test the efficiency of our algorithm. The experiments show that the algorithm is very useful for segmenting the tumor region of liver CT images. It is extremely important for calculating tumor volume and clinical treatment of the liver tumor.",

keywords = "Dynamic adaptive region growing, Liver CT, Morphological filtering, Tumor segmentation",

author = "Hong Song and Yong Wang and Huang, {Xiao Chuan} and Li, {Jia Jia} and Zhang, {Chun Meng}",

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AU - Song, Hong

AU - Wang, Yong

AU - Huang, Xiao Chuan

AU - Li, Jia Jia

AU - Zhang, Chun Meng

PY - 2014/1

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N2 - A novel algorithm is proposed to segment the tumor region of human liver CT image. Firstly, the region of interest (ROI) is segmented using the dynamic adaptive region growing method. Then the wormhole of the ROI is filled by morphological filtering to get the tumor region. Groups of CT images are used to test the efficiency of our algorithm. The experiments show that the algorithm is very useful for segmenting the tumor region of liver CT images. It is extremely important for calculating tumor volume and clinical treatment of the liver tumor.

AB - A novel algorithm is proposed to segment the tumor region of human liver CT image. Firstly, the region of interest (ROI) is segmented using the dynamic adaptive region growing method. Then the wormhole of the ROI is filled by morphological filtering to get the tumor region. Groups of CT images are used to test the efficiency of our algorithm. The experiments show that the algorithm is very useful for segmenting the tumor region of liver CT images. It is extremely important for calculating tumor volume and clinical treatment of the liver tumor.

KW - Dynamic adaptive region growing

KW - Liver CT

KW - Morphological filtering

KW - Tumor segmentation

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JF - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology

IS - 1

ER -

A dynamic adaptive region growing segmentation algorithm for tumor of liver CT images

Abstract

Keywords

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