Automatic Segmentation of Liver Structure in CT Images Using a Neural Network
Summary :
This paper describes a segmentation method of liver structure from abdominal CT images using a three–layered neural network (NN). Before the NN segmentation, preprocessing is employed to locally enhance the contrast of the region of interest. Postprocessing is also automatically applied after the NN segmentation in order to remove the unwanted spots and smooth the detected boundary. To evaluate the performance of the proposed method, the NN–determined boundaries are compared with those traced by two highly trained surgeons. Our preliminary results show that the proposed method has potential utility in automatic segmentation of liver structure and other organs in the human body.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E77-A No.11 pp.1892-1895
- Publication Date
- 1994/11/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section LETTER (Special Section of Letters Selected from the 1994 IEICE Spring Conference)
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Du–Yih TSAI, "Automatic Segmentation of Liver Structure in CT Images Using a Neural Network" in IEICE TRANSACTIONS on Fundamentals,
vol. E77-A, no. 11, pp. 1892-1895, November 1994, doi: .
Abstract: This paper describes a segmentation method of liver structure from abdominal CT images using a three–layered neural network (NN). Before the NN segmentation, preprocessing is employed to locally enhance the contrast of the region of interest. Postprocessing is also automatically applied after the NN segmentation in order to remove the unwanted spots and smooth the detected boundary. To evaluate the performance of the proposed method, the NN–determined boundaries are compared with those traced by two highly trained surgeons. Our preliminary results show that the proposed method has potential utility in automatic segmentation of liver structure and other organs in the human body.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e77-a_11_1892/_p
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@ARTICLE{e77-a_11_1892,
author={Du–Yih TSAI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Automatic Segmentation of Liver Structure in CT Images Using a Neural Network},
year={1994},
volume={E77-A},
number={11},
pages={1892-1895},
abstract={This paper describes a segmentation method of liver structure from abdominal CT images using a three–layered neural network (NN). Before the NN segmentation, preprocessing is employed to locally enhance the contrast of the region of interest. Postprocessing is also automatically applied after the NN segmentation in order to remove the unwanted spots and smooth the detected boundary. To evaluate the performance of the proposed method, the NN–determined boundaries are compared with those traced by two highly trained surgeons. Our preliminary results show that the proposed method has potential utility in automatic segmentation of liver structure and other organs in the human body.},
keywords={},
doi={},
ISSN={},
month={November},}
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TY - JOUR
TI - Automatic Segmentation of Liver Structure in CT Images Using a Neural Network
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1892
EP - 1895
AU - Du–Yih TSAI
PY - 1994
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E77-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 1994
AB - This paper describes a segmentation method of liver structure from abdominal CT images using a three–layered neural network (NN). Before the NN segmentation, preprocessing is employed to locally enhance the contrast of the region of interest. Postprocessing is also automatically applied after the NN segmentation in order to remove the unwanted spots and smooth the detected boundary. To evaluate the performance of the proposed method, the NN–determined boundaries are compared with those traced by two highly trained surgeons. Our preliminary results show that the proposed method has potential utility in automatic segmentation of liver structure and other organs in the human body.
ER -
English
