Robust statistical registration of 3D ultrasound images using texture information (original) (raw)
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Image registration plays a crucial role for the accurate reconstruction of an organ from partial ultrasound volumes and the subsequent accurate resection of a lesion/tumor with an optimally minimal damage of the healthy tissue. With the help of the Insight Toolkit (ITK), various state-of-the-art voxel-based 3D image registration algorithms were investigated, implemented and evaluated, allowing for the assessment of an accurate ultrasound image registration scheme. The investigation of the 3D space was based on an investigation of the 2D space, where the image registration components showing low performance were sorted out. The performance was assessed by calculating the standard deviation (SD) of the resulting difference images. Overall the mutual information and joint histogram based metrics showed low performance (2D-SD up to 25,9), whereas the Powell direction set algorithm in combination with the mean squares metric showed a better performance (3D-SD: 22,4).
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International Journal of Radiation Oncology*Biology*Physics, 2005
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Measurement Science and Technology, 2010
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Robust registration of volumetric image data
Head motion during fMRI experiments continues to be a significant problem for analysis, producing artifacts that can severely degrade image quality and make interpretation difficult and inaccurate. Such movement artifacts can lead to reduced statistical significance when detecting true activation or may lead to the creation of spurious activations. To address the problem of interscan motion, a retrospective image registration method has been developed. The registration technique is based on the use of non-linear deformation fields, the least-trimmed-squares robust estimator and Procrustes analysis. The registration algorithm was validated using simulated anatomical MRI volumes and real fMRI datasets. The registration technique is robust in the presence of large amounts of noise; and the experiments show that the method gives accurate estimations of motion up to 5 mm translation in all three directions and 5 degrees rotation around the three axes. The correction procedure also yields...
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Two image registration methods of different classes are evaluated and compared in this paper. From the feature based methods, the chosen algorithm was the ICP (Iterative Closest Point) [1], which is one of the most commonly used image registration algorithms in 2D and 3D applications. From the area based methods, the studied algorithm permits the registration of images with different intensities since it simultaneously estimates the transformation parameters and the image normalization. In this paper, this method will be referred to as SRIN (Simultaneous Registration and Intensity Normalization) [2]. Since these two methods are from different nature, the SRIN method will be applied in intensity images created from the same features used by the ICP method. In this way, the SRIN method avoids the step of feature correspondence. Experimental results demonstrate that the SRIN algorithm has an excellent convergence capacity and registration precision using a variety of different images a...
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A generalized, accurate, automatic, retrospective method of image registration for three-dimensional images has been developed. The method is based on mutual information, a specific measure of voxel similarity, and is applicable to a wide range of imaging modalities and organs, rigid or deformable. A drawback of mutual information-based image registration is long execution times. To overcome the speed problem, low-cost, customized hardware to accelerate this computationally intensive task was developed. Individual hardware accelerator units (each, in principle, 25-fold faster than a comparable software implementation) can be concatenated to perform image registration at any user-desired speed. A first-generation prototype board with two processing units provided a 12-to 16-fold increase in speed. Enhancements for increasing the speed further are being developed. These advances have enabled many nontraditional applications of image registration and have made the traditional applications more efficient. Clinical applications include fusion of computed tomographic (CT), magnetic resonance, and positron emission tomographic (PET) images of the brain; fusion of whole-body CT and PET images; fusion of fourdimensional spatiotemporal ultrasonographic (US) and single photon emission CT images of the heart; and correction of misalignment between pre-and poststress four-dimensional US images.
Semiautomatic registration of volumetric ultrasound scans
Ultrasound in Medicine and Biology, 1999
—We demonstrate the ability to register easily and accurately volumetric ultrasound scans without significant data preprocessing or user intervention. Two volumetric ultrasound breast scan data sets were acquired from two different patients with breast cancer. Volumetric scan data were acquired by manually sweeping a linear array transducer mounted on a linear slider with a position encoder. The volumetric data set pairs consisted of color flow and/or power mode Doppler data sets acquired serially on the same patients. A previously described semiautomatic registration method based on maximizing mutual information was used to determine the transform between data sets. The results suggest that, even for the deformable breast, three-dimensional full affine transforms can be sufficient to obtain clinically useful registrations; warping may be necessary for increased registration accuracy. In conclusion, mutual information-based automatic registration as implemented on modern workstations is capable of yielding clinically useful registrations in times <35 min.
Probabilistic registration of 3-D medical images
… Tech. Rep. CMU-RI-TR-99 …
The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the US government. ... Registration between 3-D images of human anatomies enables cross- ...