Abstract
Liver extraction from medical images like CT scan and MR images is a challenging task. There are many manuals, Semi-automatic and automatic methods available to extract the liver from computerized tomography (CT) scan images and MR images. However, no method is available in the literature to extract the liver from Magnetic Resonance Cholangio-pancreatography (MRCP) images. Extracting the liver accurately from MRCP images is needed, so that the physician can diagnose the disease easily and plan preoperative liver surgery accordingly. In this paper, we propose a liver extraction method based on Graph Cut algorithm for liver extraction from MRCP images. The experimental results show that the proposed method is very effective for liver extraction from MRCP images.
Highlights
The healthy body depends on the healthy liver
We developed an automatic method for liver extraction from Magnetic Resonance Cholangiopancreatography (MRCP) images
In order to fill the gap, a liver extraction method from MRCP images is proposed in this paper
Summary
The healthy body depends on the healthy liver. There are many metabolic functions that performed by the liver for the smooth working of other organs. Due to the rapidly increase in the use of MRCP imaging technology an accurate and efficient liver extraction method from MRCP images is needed. An accurate liver extraction will help the radiologist and surgeon in diagnosing the liver diseases and in the planning of preoperative liver surgery as well. Liver extraction is very important stage in diagnosing the liver diseases. Most of the research work for CT scan and MRI images has been conducted on liver extraction. Different type of method like manual, Semi-automatic and automatic methods are available to extract the liver from CT scan images and MR images [5]-[12]. We developed an automatic method for liver extraction from MRCP images. In order to fill the gap, a liver extraction method from MRCP images is proposed in this paper.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
