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Hierarchical Organ Segmentation using Location Information based on Multi-atlas in Abdominal CT Images

복부 컴퓨터단층촬영 영상에서 다중 아틀라스 기반 위치적 정보를 사용한 계층적 장기 분할

  • Kim, Hyeonjin (Dept. of Software Convergence, Seoul Women's University) ;
  • Kim, Hyeun A (Dept. of Software Convergence, Seoul Women's University) ;
  • Lee, Han Sang (School of Electrical Engineering, Korea Advanced Institute of Science and Technology) ;
  • Hong, Helen (Dept. of Software Convergence, Seoul Women's University)
  • Received : 2016.10.10
  • Accepted : 2016.12.03
  • Published : 2016.12.30

Abstract

In this paper, we propose an automatic hierarchical organ segmentation method on abdominal CT images. First, similar atlases are selected using bone-based similarity registration and similarity of liver, kidney, and pancreas area. Second, each abdominal organ is roughly segmented using image-based similarity registration and intensity-based locally weighted voting. Finally, the segmented abdominal organ is refined using mask-based affine registration and intensity-based locally weighted voting. Especially, gallbladder and pancreas are hierarchically refined using location information of neighbor organs such as liver, left kidney and spleen. Our method was tested on a dataset of 12 portal-venous phase CT data. The average DSC of total organs was $90.47{\pm}1.70%$. Our method can be used for patient-specific abdominal organ segmentation for rehearsal of laparoscopic surgery.

Keywords

References

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