Image Registration: A Review of Elastic Registration Methods Applied to Medical Imaging
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paper_title: Image Registration using Fractional Fourier Transform

paper_content:

This image registration (IR) is a fundamental task in many image processing applications such as medical diagnosis, satellite imaging, super-resolution image reconstruction etc. Fourier transform based methods have also been in use for IR purposes for both the shifted and rotated images using the phase correlation method (Brown, 1992). As fractional Fourier transform (FRFT) is a generalization of the conventional Fourier transform, it is natural to extend its use in IR applications. In this paper, the authors propose the use of the FRFT in IR problems involving either linear shifts or pure rotations in the given images to be registered. Simulation results of the proposed techniques are also presented
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paper_title: Intra-subject Elastic Registration of 3D Ultrasound Images

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Abstract 3D registration of ultrasound images is an important and fast-growing research area with various medical applications, such as image-guided radiotherapy and surgery. However, this registration process remains extremely challenging due to the deformation of soft tissue and the existence of speckles in these images. This paper presents a technique for intra-subject, intra-modality elastic registration of 3D ultrasound images. Using the general concept of attribute vectors, we define the corresponding voxels in the fixed and moving images. Our method does not require presegmentation and does not employ any numerical optimization procedure. As the computational requirements are minimal, the method has potential use in real-time applications. The technique is implemented and tested on 3D ultrasound images of human liver, captured by a 3D ultrasound transducer. The results show that the method is sufficiently accurate and robust even in cases where artifacts such as shadows exist in the ultrasound data.
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paper_title: Nonrigid registration using free-form deformations: application to breast MR images

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In this paper the authors present a new approach for the nonrigid registration of contrast-enhanced breast MRI. A hierarchical transformation model of the motion of the breast has been developed. The global motion of the breast is modeled by an affine transformation while the local breast motion is described by a free-form deformation (FFD) based on B-splines. Normalized mutual information is used as a voxel-based similarity measure which is insensitive to intensity changes as a result of the contrast enhancement. Registration is achieved by minimizing a cost function, which represents a combination of the cost associated with the smoothness of the transformation and the cost associated with the image similarity. The algorithm has been applied to the fully automated registration of three-dimensional (3-D) breast MRI in volunteers and patients. In particular, the authors have compared the results of the proposed nonrigid registration algorithm to those obtained using rigid and affine registration techniques. The results clearly indicate that the nonrigid registration algorithm is much better able to recover the motion and deformation of the breast than rigid or affine registration algorithms.
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paper_title: Segmentation of ultrasound images by using wavelet transform

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This paper presents a new feature extraction method for the segmentation of ultrasound images. Wavelet transform is proposed for determination of the textures in the ultrasound images. Elements of the feature vectors are formed by the wavelet coefficients at several decomposition level. In this study, incremental self-organized neural network (INeN) is proposed as the classifier. The classification performance is increased by using the wavelet transform and the INeN together.
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paper_title: A review of cardiac image registration methods

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In this paper, the current status of cardiac image registration methods is reviewed. The combination of information from multiple cardiac image modalities, such as magnetic resonance imaging, computed tomography, positron emission tomography, single-photon emission computed tomography, and ultrasound, is of increasing interest in the medical community for physiologic understanding and diagnostic purposes. Registration of cardiac images is a more complex problem than brain image registration because the heart is a nonrigid moving organ inside a moving body. Moreover, as compared to the registration of brain images, the heart exhibits much fewer accurate anatomical landmarks. In a clinical context, physicians often mentally integrate image information from different modalities. Automatic registration, based on computer programs, might, however, offer better accuracy and repeatability and save time.
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paper_title: Robust registration for computer-integrated orthopedic surgery: Laboratory validation and clinical experience

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Abstract In order to provide navigational guidance during computer-integrated orthopedic surgery, the anatomy of the patient must first be registered to a medical image or model. A common registration approach is to digitize points from the surface of a bone and then find the rigid transformation that best matches the points to the model by constrained optimization. Many optimization criteria, including a least-squares objective function, perform poorly if the data include spurious data points (outliers). This paper describes a statistically robust, surface-based registration algorithm that we have developed for orthopedic surgery. To find an initial estimate, the user digitizes points from predefined regions of bone that are large enough to reliably locate even in the absence of anatomic landmarks. Outliers are automatically detected and managed by integrating a statistically robust M -estimator with the iterative-closest-point algorithm. Our in vitro validation method simulated the registration process by drawing registration data points from several sets of densely digitized surface points. The method has been used clinically in computer-integrated surgery for high tibial osteotomy, distal radius osteotomy, and excision of osteoid osteoma.
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paper_title: A fast image registration technique for motion artifact reduction in DSA

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In digital subtraction angiography (DSA), patient motion is the primary cause of image quality degradation. The motion correction algorithms developed so far were not sufficiently fast so as to be suitable for integration in a clinical setting. In this paper we describe a new image registration technique for motion artifact reduction in DSA which is fully automatic, effective, and computationally very efficient. Using an image content driven control point selection mechanism and modern graphics hardware for image warping, the algorithm requires less than one second per DSA image (on average). Preliminary experiments on cerebral DSA images illustrate the applicability of the technique.
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paper_title: Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN)

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When lung nodules overlap with ribs or clavicles in chest radiographs, it can be difficult for radiologists as well as computer-aided diagnostic (CAD) schemes to detect these nodules. In this paper, we developed an image-processing technique for suppressing the contrast of ribs and clavicles in chest radiographs by means of a multiresolution massive training artificial neural network (MTANN). An MTANN is a highly nonlinear filter that can be trained by use of input chest radiographs and the corresponding "teaching" images. We employed "bone" images obtained by use of a dual-energy subtraction technique as the teaching images. For effective suppression of ribs having various spatial frequencies, we developed a multiresolution MTANN consisting of multiresolution decomposition/composition techniques and three MTANNs for three different-resolution images. After training with input chest radiographs and the corresponding dual-energy bone images, the multiresolution MTANN was able to provide "bone-image-like" images which were similar to the teaching bone images. By subtracting the bone-image-like images from the corresponding chest radiographs, we were able to produce "soft-tissue-image-like" images where ribs and clavicles were substantially suppressed. We used a validation test database consisting of 118 chest radiographs with pulmonary nodules and an independent test database consisting of 136 digitized screen-film chest radiographs with 136 solitary pulmonary nodules collected from 14 medical institutions in this study. When our technique was applied to nontraining chest radiographs, ribs and clavicles in the chest radiographs were suppressed substantially, while the visibility of nodules and lung vessels was maintained. Thus, our image-processing technique for rib suppression by means of a multiresolution MTANN would be potentially useful for radiologists as well as for CAD schemes in detection of lung nodules on chest radiographs.
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paper_title: A Survey of Medical Image Registration

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The purpose of this paper is to present a survey of recent (published in 1993 or later) publications concerning medical image registration techniques. These publications will be classified according to a model based on nine salient criteria, the main dichotomy of which is extrinsic versus intrinsic methods. The statistics of the classification show definite trends in the evolving registration techniques, which will be discussed. At this moment, the bulk of interesting intrinsic methods is based on either segmented points or surfaces, or on techniques endeavouring to use the full information content of the images involved.
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paper_title: Fast parametric elastic image registration

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We present an algorithm for fast elastic multidimensional intensity-based image registration with a parametric model of the deformation. It is fully automatic in its default mode of operation. In the case of hard real-world problems, it is capable of accepting expert hints in the form of soft landmark constraints. Much fewer landmarks are needed and the results are far superior compared to pure landmark registration. Particular attention has been paid to the factors influencing the speed of this algorithm. The B-spline deformation model is shown to be computationally more efficient than other alternatives. The algorithm has been successfully used for several two-dimensional (2-D) and three-dimensional (3-D) registration tasks in the medical domain, involving MRI, SPECT, CT, and ultrasound image modalities. We also present experiments in a controlled environment, permitting an exact evaluation of the registration accuracy. Test deformations are generated automatically using a random hierarchical fractional wavelet-based generator.
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paper_title: A hierarchical approach to elastic registration based on mutual information

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Abstract A hierarchical approach to elastic registration based on mutual information, in which the images are progressively subdivided, locally registered, and elastically interpolated, is presented. To improve the registration, a combination of prior and floating information on the joint probability is proposed. It is shown that such a combination increases the registration speed at the coarser levels in hierarchy, enables a registration of finer details, and provides additional guidance to the optimisation process. Besides, a threefold local registration consistency test and correction of shading were employed to increase the overall registration performance. The proposed hierarchical method for elastic registration was tested on an experimental database of 2D images of histochemically differently stained serial cross-sections of human skeletal muscle. The obtained results show that 95% of the images could be successfully registered. The inclusion of prior information is an important break through that may enable routine use of the mutual information cost function in a variety of 2D and 3D image registration algorithms in the future.
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paper_title: Elastic Medical Image Registration Based on Image Intensity

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A two-step elastic medical image registration approach is proposed, which is based on the image intensity. In the first step, the global affine medical image registration is used to establish one-to-one mapping between the two images to be registered. After this first step, the images are registered up to small local elastic deformation. Then the mapped images are used as inputs in the second step, during which, the study image is modeled as elastic sheet by being divided into several subimages. Moving the individual subimage in the reference image, the local displacement vectors are found and the global elastic transformation is achieved by assimilating all of the local transformation into a continuous transformation. This algorithm has been tested on both simulated and tomographic images.
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paper_title: 3D Registration of Ultrasound Images Based on Morphology Skeleton

paper_content:

In order to eliminate displacement and elastic deformation between images of adjacent frames in course of 3D ultrasonic image reconstruction, elastic registration based on morphology skeleton was adopted in this paper. Feature points of connected skeleton are extracted automatically by accounting topical curvature extreme points several times. Initial registration is processed according to barycenter of skeleton. Whereafter, elastic registration based on radial basis function are processed according to feature points of skeleton. Result of example demonstrate that according to traditional rigid registration, elastic registration based on skeleton feature retain natural difference in shape for organ's different part, and eliminate slight elastic deformation between frames caused by image obtained process simultaneously. This algorithm has a high practical value for image registration in course of 3D ultrasound image reconstruction
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paper_title: Automatic hybrid registration for 2-dimensional CT abdominal images

paper_content:

Registration of abdominal images plays an important role in clinical practice, however, because of the complex deformations of organ structure and volume, abdominal image registration remains a challenge. In this paper, a hybrid registration approach is proposed, which consists of two procedures: intensity-based registration procedure and landmark-based registration procedure. In intensity-based registration, in order to speed up registration convergence and to improve registration computation efficiency, a wavelet-based hierarchical method is proposed, in which the global displacements are corrected using mutual information algorithm. In the landmark-based registration, firstly, the landmark points are selected automatically; and then, the local non-linear deformations are corrected using the elastically thin-plate splines. By combining the advantages of intensity-based registration method and that of landmark-based method, the proposed approach can register the images accurately and efficiently. The registration performance of the proposed algorithm is validated by experiments on clinical computed tomography (CT) abdominal images.
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paper_title: Medical image registration

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Radiological images are increasingly being used in healthcare and medical research. There is, consequently, widespread interest in accurately relating information in the different images for diagnosis, treatment and basic science. This article reviews registration techniques used to solve this problem, and describes the wide variety of applications to which these techniques are applied. Applications of image registration include combining images of the same subject from different modalities, aligning temporal sequences of images to compensate for motion of the subject between scans, image guidance during interventions and aligning images from multiple subjects in cohort studies. Current registration algorithms can, in many cases, automatically register images that are related by a rigid body transformation (i.e. where tissue deformation can be ignored). There has also been substantial progress in non-rigid registration algorithms that can compensate for tissue deformation, or align images from different subjects. Nevertheless many registration problems remain unsolved, and this is likely to continue to be an active field of research in the future.
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paper_title: Evaluation of hierarchical elastic medical image registration method

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The paper investigates the hierarchical approach to elastic medical image registration based on mutual information (MI) (Likar, B. and Pernus, F., Image and Vision Computing, vol.19, p.33-44, 2001), in which images are progressively subdivided, locally registered, and elastically interpolated using a thin-plate spline. The technique has been shown to be efficient and robust with small local transformations. However, problems do exist with this technique. First, MI is a statistical property of the two images, so the reduction in the number of samples due to the partitioning of the images into smaller sub-images reduces the statistical quality of the joint intensity histogram. Also, the partitioning scheme may lose some important information, such as edges, which lie exactly on the partition. The statistical problem of MI is resolved by resampling and combining with global MI. An overlapping scheme is implemented in which the image is subdivided into sub-images which overlap their neighbours. This helps to overcome the edge problems. Experiments show that these two methods can improve the registration results to some limited extent (PSNR) and the visual result is much better, especially for the overlapping window scheme.
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paper_title: Image registration using hierarchical B-splines

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Hierarchical B-splines have been widely used for shape modeling since their discovery by Forsey and Bartels. We present an application of this concept, in the form of free-form deformation, to image registration by matching two images at increasing levels of detail. Results using MRI brain data are presented that demonstrate high degrees of matching while unnecessary distortions are avoided. We compare our results with the nonlinear ICP (iterative closest point) algorithm (used for landmark-based registration) and optical flow (used for intensity-based registration).
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paper_title: Image Registration using Fractional Fourier Transform

paper_content:

This image registration (IR) is a fundamental task in many image processing applications such as medical diagnosis, satellite imaging, super-resolution image reconstruction etc. Fourier transform based methods have also been in use for IR purposes for both the shifted and rotated images using the phase correlation method (Brown, 1992). As fractional Fourier transform (FRFT) is a generalization of the conventional Fourier transform, it is natural to extend its use in IR applications. In this paper, the authors propose the use of the FRFT in IR problems involving either linear shifts or pure rotations in the given images to be registered. Simulation results of the proposed techniques are also presented
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paper_title: Automatic hybrid registration for 2-dimensional CT abdominal images

paper_content:

Registration of abdominal images plays an important role in clinical practice, however, because of the complex deformations of organ structure and volume, abdominal image registration remains a challenge. In this paper, a hybrid registration approach is proposed, which consists of two procedures: intensity-based registration procedure and landmark-based registration procedure. In intensity-based registration, in order to speed up registration convergence and to improve registration computation efficiency, a wavelet-based hierarchical method is proposed, in which the global displacements are corrected using mutual information algorithm. In the landmark-based registration, firstly, the landmark points are selected automatically; and then, the local non-linear deformations are corrected using the elastically thin-plate splines. By combining the advantages of intensity-based registration method and that of landmark-based method, the proposed approach can register the images accurately and efficiently. The registration performance of the proposed algorithm is validated by experiments on clinical computed tomography (CT) abdominal images.
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paper_title: Elastic registration of 2D abdominal CT images using hybrid feature point selection for liver lesions

paper_content:

Abdominal CT images have distinct intensity distribution. This feature is used to correct local deformations in the image. Reference and study images are decomposed using wavelet decomposition. Global deformations are first corrected applying rigid registration by use of maximization of Mutual Information as the similarity measure at each level of registration hierarchy. Initially registered image and reference image are further elastically registered using landmark based elastic registration. Here landmarks or feature points are obtained by first intensity thresholding the images followed by boundary selection to obtain lesion boundaries and finally obtaining the centroid and convex hull points of lesions within the images. Convex hull points that lie on the boundary of lesions coupled with centroids of lesions are helpful in precisely identifying the lesions. An advantage of this is that lesions are enhanced to allow for deformations to be precisely determined. This is useful in improving diagnostic accuracy. The performance of algorithm is tested on a real case study of abdominal CT images with liver abscess. Considerable improvement in correlation coefficient and Signal to Noise ratio of the two images is observed.
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Title: Image Registration: A Review of Elastic Registration Methods Applied to Medical Imaging

Section 1: INTRODUCTION
Description 1: Provide an overview of image registration, its objectives, and applications in various fields including medical imaging.

Section 2: Image registration in medical imaging
Description 2: Explore the historical growth, significance, and different applications of image registration in the field of medical imaging.

Section 3: Rigid and Elastic registration
Description 3: Discuss the differences between rigid and elastic registration, and their specific applications within medical imaging.

Section 4: ELASTIC REGISTRATION APPLIED TO MEDICAL IMAGING
Description 4: Examine various methods and approaches used for elastic registration in medical imaging, including specific cases and studies.

Section 5: METHODOLOGY USED
Description 5: Detail the methodology adopted for hybrid image registration, highlighting key processes such as initial registration, segmentation, and elastic registration.

Section 6: EXPERIMENTAL RESULTS
Description 6: Present the results obtained from the experimental implementation of the discussed methodologies.