Multiresolution Image Registration in Digital X-Ray Angiography with Intensity Variation Modeling

Image registration between planning CT images and cone beam-CT (CBCT) images is one of the key technologies of image guided radiotherapy (IGRT). Current image registration methods fall roughly into two categories: geometric features-based and image grayscale-based. Mutual information (MI) based registration, which belongs to the latter category, has been widely applied to multi-modal and mono-modal image registration. However, the standard mutual information method only focuses on the image intensity information and overlooks spatial information, leading to the instability of intensity interpolation. Due to its use of positional information, wavelet transform has been applied to image registration recently. In this study, we proposed an approach to setup CT and cone beam-CT (CBCT) image registration in radiotherapy based on the combination of mutual information (MI) and stationary wavelet transform (SWT). Firstly, SWT was applied to generate gradient images and low frequency components produced in various levels of image decomposition were eliminated. Then inverse SWT was performed on the remaining frequency components. Lastly, the rigid registration of gradient images and original images was implemented using a weighting function with the normalized mutual information (NMI) being the similarity measure, which compensates for the lack of spatial information in mutual information based image registration. Our experiment results showed that the proposed method was highly accurate and robust, and indicated a significant clinical potential in improving the accuracy of target localization in image guided radiotherapy (IGRT).

show abstract

“…Root mean square error (MSE), which is defined as follows, is employed as the registration error [26–29]. …”

Section: Resultsmentioning

confidence: 99%

A Stationary Wavelet Transform Based Approach to Registration of Planning CT and Setup Cone beam-CT Images in Radiotherapy

et al. 2014

View full text Add to dashboard Cite

show abstract

“…The aim is to evaluate the preservation of local structures. Since PABSM is inspired from the subtraction-based methods, PABSM will also be compared with methods, namely, multi-resolution registration-based method (MRRBM) [42], motion coherency constraint-based method (MCCBM) [23] and stochastic optimization-based method (SOBM) [5]. The precision-recall curve is utilized to quantitatively evaluate the preservation of vascular structures in the images obtained by the methods, namely, LBM, LPBM, BBM, MRRBM, MCCBM, SOBM and the proposed PABSM, on clinical data.…”

Section: B Experiments Designmentioning

confidence: 99%

Patch-Based Adaptive Background Subtraction for Vascular Enhancement in X-Ray Cineangiograms

Song

Frangi

Yang

et al. 2019

IEEE J. Biomed. Health Inform.

View full text Add to dashboard Cite

Objective: Automatic vascular enhancement in Xray cineangiography is of crucial interest, for instance, for better visualizing and quantifying coronary arteries in diagnostic and interventional procedures. Methods: a novel patch-based adaptive background subtraction method (PABSM) is proposed automatically enhancing vessels in coronary X-ray cineangiography. First, pixels in the cineangiogram is described by the vesselness and Gabor features. Second, a classifier is utilized to separate the cineangiogram into the rough vascular and non-vascular region. Dilation is applied to the classified binary image to include more vascular region. Third, a patch-based background synthesis is utilized to fill the removed vascular region. Results: a database containing 320 cineangiograms of 175 patients was collected, and then an interventional cardiologist annotated all vascular structures. The performance of PABSM is compared with six state-of-the-art vascular enhancement methods regarding the precision-recall curve and Cvalue. The area under the precision-recall curve is, and the C-value is . Conclusion: PABSM can automatically enhance the coronary artery in the cineangiograms. It preserves the integrity of vascular topological structures, particularly in complex vascular regions and removes noise caused by the non-uniform gray level distribution in the cineangiogram. Significance: PABSM can avoid the motion artifacts and eases the subsequent vascular segmentation, which is crucial for the diagnosis and interventional procedures of coronary artery diseases.

show abstract

“…The proposed deep motion tracking (DMT) method will be compared with the techniques, viz. Multi-resolution image registration (MIR) (Nejati et al, 2014), DeepFlow (Weinzaepfel et al, 2013) and EpicFlow (Revaud et al, 2015), using a set of matching points. The points are manually labelled 295…”

Section: B) Evaluation Criteriamentioning

confidence: 99%

Deep motion tracking from multiview angiographic image sequences for synchronization of cardiac phases

Song

Du²,

Liu³

et al. 2019

Phys. Med. Biol.

View full text Add to dashboard Cite

In the diagnosis and interventional treatment of coronary artery disease, the 3D time reconstruction of the coronary artery on the basis of X-ray angiographic image sequences can provide dynamic structural information. The synchronization of cardiac phases in the sequences 15 is essential for minimizing the influence of cardiorespiratory motion and realizing precise 3D time reconstruction. Key points are initially extracted from the first image of a sequence. Matching grid points between consecutive images in the sequence are extracted by a multi-layer matching strategy. Then deep motion tracking of key points is achieved by local deformation based on the neighboring grid points of key points. The local deformation is optimized by the Random 20Sample Consensus algorithm. Then, a simple harmonic motion model is utilized to distinguish cardiac motion from other motion sources (e.g. respiratory, patient movement, etc.). Next, the signal which is composed of cardiac motions is filtered by a band-pass filter to reconstruct the cardiac phases. Finally, the synchronization of cardiac phases from different imaging angles is realized by piece-wise linear transformation. The proposed method was evaluated using clinical X-ray angio-25 graphic image sequences from 13 patients. matching points can be accurately computed by the deep motion tracking method. The mean peak temporal distance between the reconstructed cardiac phases and the electrocardiograph signal is s. The correlation between the cardiac phases of the same patient is over . Compared with three other state-of-the-art methods, the proposed method accurately reconstructs and synchronizes the cardiac phases from different sequences of the 30 same patient. The proposed deep motion tracking method is robust and highly effective in synchronizing cardiac phases of angiographic image sequences captured from different imaging angles.

show abstract

Multiresolution Image Registration in Digital X-Ray Angiography with Intensity Variation Modeling

Cited by 25 publications

References 23 publications

A Stationary Wavelet Transform Based Approach to Registration of Planning CT and Setup Cone beam-CT Images in Radiotherapy

A Stationary Wavelet Transform Based Approach to Registration of Planning CT and Setup Cone beam-CT Images in Radiotherapy

Patch-Based Adaptive Background Subtraction for Vascular Enhancement in X-Ray Cineangiograms

Deep motion tracking from multiview angiographic image sequences for synchronization of cardiac phases

Contact Info

Product

Resources

About