An optimal liver segmentation method in MRI images using adaptive water flow model

Subject Areas :

Marjan Heidari ¹ , Mehdi Taghizadeh ² , Hassan Masoumi ³ , مرتضی ولی زاده ⁴

1 - Department of Electrical and Computer Engineering, Kazerun Branch, Islamic Azad University, Kazerun, Iran
2 - Faculty of Electrical and Computer, Kazerun Branch, Islamic Azad University
3 - Department of Electrical and Computer Engineering, Kazerun Branch, Islamic Azad University, Kazerun, Iran
4 - دانشکده برق و کامپیوتر، دانشگاه ارومیه، ارومیه، ایران

Received: 2023-08-19 Accepted : 2023-12-03 Published : 2023-12-10

Keywords: Liver segmentation, adaptive water flow, MRI image, areas classification ,

Abstract :

Liver segmentation in medical images is still considered as a challenge in computer diagnosis systems. In this paper, an optimal algorithm based on the adaptive water flow model for segmentation is introduced. This algorithm first processes the image by means of a transfer function designed based on the probability distribution function of the brightness levels of the liver pixels to distinguish the liver region from the rest of the parts. Then, with the help of the rainfall algorithm, which is controlled based on the spatial information and light levels of the liver, possible areas of the liver are extracted, and further, the possible areas of the liver are classified with a layered perceptron neural network, using shape and texture features. Classification of areas instead of pixels has increased the efficiency of the algorithm. The obtained experimental results show a far more appropriate performance in comparison with other evaluation algorithms

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