Master thesis
My Master of Engineering master thesis "Liver Perfusion using Level Set
Methods" has been written in between September 2004 and May 2005 at the
Shanghai Jiaotong University under the
supervision of Professor Lixu Gu at the Medical Image Processing and
Visualization laboratories.
The thesis was graded excellent.
Abstract
The clinical process known as liver perfusion is a well-established method to
determine blood flow conditions. For certain illnesses related to the liver,
information about the blood flow to the liver can help in obtaining an
accurate diagnosis. The process is then called liver perfusion and works as
follows. A series of MRI images of the patients abdomen is obtained in
regular time intervals. At some point, a contrast agent is injected into the
patients blood circuit, creating a visible response in the MRI. By tracking
the response at the liver, the perfusion intensity curve over time can be
deduced.
This thesis describes a novel method of automatically obtaining the
perfusion intensity curve from a series of MRI images. After a minimal
manual initialization, the system automatically segments and marks the
liver in the image and tracks the liver over time across all images. For
the segmentation - the marking of the liver shape inside the image - both
the modern Fast Marching Method and the Level Set Method are used. By
using a flexible framework combining both these methods and by choosing a
segmentation speed function carefully, a good performance is achieved in
both accuracy and runtime performance. A fully functional prototype
application demonstrating the liver perfusion measurement using minimal
manual initialization has been developed and tested.
The results are validated on more than ten real clinical series, by
feedback from radiologists and by two synthetic tests. In all
evaluations the method proves to be significantly better than the
previously used method. The improvement stems from the more careful
model being used to register images in the series; moreover efficient
interpolation methods are used to compensate for outliers, producing a
good perfusion curve.
Download