A Hybrid segmentation approach based on Neutrosophic sets and modified watershed: A case of abdominal CT liver parenchyma

Citation:
Sayed, G. I., A. E. Hassanien, M. A. Ali, and T. Gaber, "A Hybrid segmentation approach based on Neutrosophic sets and modified watershed: A case of abdominal CT liver parenchyma", IEEE iInternational Computer Engineering Conference - ICENCO , Cairo, 30 Dec, 2015.

Date Presented:

30 Dec

Liver cancer is one of the most common internal
malignancies worldwide and also one of the most leading death
causes disease. Early detection and accurate staging of liver
cancer is considered an important issue in practical radiology. In
this paper, a hybrid segmentation approach based on the modified
Watershed algorithm and Neutrosophic logics is proposed for
liver segmentation from abdominal CT images. The proposed
approach consists of three fundamental phases: (1) preprocessing,
(2) CT image transformation to Neutrosophic domain and (3)
post-processing phase. At preprocessing phase, histogram equalization
and median filter are applied to enhance the contrast
and intensity values of the liver CT image as well as removing
the noise. The enhanced CT liver image is transformed and
represented in the Neutrosophic set domain via three membership
sets. Finally, at post-processing phase, mathematical morphology
and modified watershed algorithm are used to enhance the
obtained truth image produced from the previous phase and to
extract liver from CT image. Several measurements are used to
evaluate the performance of the proposed segmentation approach.
It obtains overall accuracy almost 95%. Moreover, it compared
with other approaches and achieves better results.