Computed tomography and echocardiography image fusion technique for cardiac images
Ultrasound is used in minimally invasive cardiac procedures widely, because of its convenience and noninvasive nature. However, the low quality of ultrasound images usually limits their usefulness as a tool to guide cardiac procedures; it is often complicated to relate images to their anatomical...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/69400/1/FSKTM%202016%2045%20-%20IR.pdf |
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| Summary: | Ultrasound is used in minimally invasive cardiac procedures widely, because of its
convenience and noninvasive nature. However, the low quality of ultrasound images
usually limits their usefulness as a tool to guide cardiac procedures; it is often
complicated to relate images to their anatomical context in the heart.
For improving the interpretability of ultrasound images, where keeping ultrasound as
a flexible real time imaging and functional modality, there is a need for some
registration techniques that integrate them with their correspond context in high
quality pre-operative models, such as Computed Tomography images or Magnetic
Resonance Imaging.
In this study, a fusion system which integrates the knowledge of segmentation and
intensity into registration is presented in Computed Tomography and
Echocardiography images of heart. The goal of this thesis is integrating detected
features, segmentation result information, and intensity information from two
mentioned images, into a non-rigid registration framework, and achieve a high
quality spatial mapping.
The fusion system is developed as following:
First, multiple Echocardiography images are compounded to get a better quality
image with wider field of view. A fusion method is presented which particularly
intends to increase the segment-ability of echocardiography features such as
ventricle contours and improving their contrast. The presented method is also
capable of enhancing the contrast, decreasing the impact of echo artifacts, expanding
the field of view and improving the signal to noise ratio.
Then, a segmentation approach based on a constrained Level set method is
developed to identify the feature from Echocardiography images. It is a new
geometrically level Set algorithm for the segmentation of the endocardial contours in
echocardiographic images in presence of intensity non-uniformity. It will present an
accurate and robust segmentation technique, which its results are going to use as
input for fusion system in the following.
In last stage, non-rigid registration is applied using segmentation result information
plus intensity information from two images and a consistent transformation to match
these features together is calculated.
The proposed fusion system can use for medical interventions, for better
physiological understanding, effective image guidance surgery, treatment,
monitoring and diagnostic purposes, through finding spatial mapping between two
images, to observe the changes of anatomical structure and to merge the information
from multiple modalities.
As it will be discussed in detail in the thesis, for input image, the proposed technique
is unable in accurate segmentation in many instances at end diastole (87.3%) and
over half the time at end-systole (61.7%). However, for fused images, it is unable to
detect accurate segmentation 24.6% of times at end diastole, whilst there was just
one failing at end systole (3.1%). It means fusion results in enhanced image quality
consequently leads to effective ventricles segmentation.
For evaluation, beside uncertainty estimation and visually evaluation by experts,
quantitative and qualitative evaluations are conducted. For measuring the accuracy
quantitatively, target registration error (TRE) is calculated before and after the
registration, then a comparison is made. Also, different performance metrics are
implemented to examine the performance of the proposed fusion system.
For further studies, the combined navigation system can be designed for real-time
surgery guidance. Furthermore, integrating virtual models and echocardiographic
images will provide a potential means for giving image-guidance for processes
which include both functional and anatomical imaging.
Another direction for further study will be doing the registration for whole cardiac
cycle: applying temporal synchronization between CT and echocardiography which
is achieved by using ECG signals. Visualization of the result can be investigated
further, as well. |
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