Intra-subject elastic registration of 3D ultrasound images

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 is extremely challenging due to the deformation of soft tissue and the existence of speckles in these images. This paper presents a novel intra-modality elastic registration technique for 3D ultrasound images. It uses the general concept of attribute vectors to find the corresponding voxels in the fixed and moving images. The method does not require any pre-segmentation and does not employ any numerical optimization procedure. Therefore, the computational requirements are very low and it has the potential to be used for real-time applications. The technique is implemented and tested for 3D ultrasound images of liver, captured by a 3D ultrasound transducer. The results show that the method is sufficiently accurate and robust and is not easily trapped with local minima.

Manuscript A Modified HAMMER Algorithm for Deformable Registration of Ultrasound Images

Abstract. A new technique for elastic registration of ultrasound images is proposed and evaluated. The algorithm is fast and robust, and has potential for intra-operative applications. It is a modified version of HAMMER technique, which was developed to elastically register magnetic resonance images of brain. A general concept of attribute vectors is employed to find correspondence across images, and new elements are suggested for the vectors to be able to distinguish between different features in ultrasound images. Registration results of simulated and actual deformation of ultrasound images of liver are presented

Towards real-time registration of 4D ultrasound images

Abstract — In this paper, we demonstrate a method for fast registration of sequences of 3D liver images, which could be used for the future real-time applications. In our method, every image is elastically registered to a so called fixed ultrasound image exploiting the information from previous registration. A few feature points are automatically selected, and tracked inside the images, while the deformation of other points are extrapolated with respect to the tracked points employing a fast free-form approach. The main intended application of the proposed method is real-time tracking of tumors for radiosurgery. The algorithm is evaluated on both naturally and artificially deformed images. Experimental results show that for around 85 percent accuracy, the process of tracking is completed very close to real time. I

Multi-slice to volume registration of ultrasound data to a statistical atlas of human pelvis.

Identifying the proper orientation of the pelvis is a critical step in accurate placement of the femur prosthesis in the acetabulum in Total Hip Replacement (THR) surgeries. The general approach to localize the orientation of the pelvis coordinate system is to use X-ray fluoroscopy to guide the procedure. An alternative can be employing intra-operative ultrasound (US) imaging with pre-operative CT scan or fluoroscopy imaging. In this paper, we propose to replace the need of pre-operative imaging by using a statistical shape model of the pelvis, constructed from several CT images. We then propose an automatic deformable intensity-based registration of the anatomical atlas to a sparse set of 2D ultrasound images of the pelvis in order to localize its anatomical coordinate system. In this registration technique, we first extract a set of 2D slices from a single instance of the pelvic atlas. Each individual 2D slice is generated based on the location of a corresponding 2D ultrasound image. Next, we create simulated ultrasound images out of the 2D atlas slices and calculate a similarity metric between the simulated images and the actual ultrasound images. The similarity metric guides an optimizer to generate an instance of the atlas that best matches the ultrasound data. We demonstrated the feasibility of our proposed approach on two male human cadaver data. The registration was able to localize a patient-specific pelvic coordinate system with origin translation error of 2 mm and 3.45 mm, and average axes rotation error of 3.5 degrees and 3.9 degrees for the two cadavers, respectively. Copyright 2010 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofReviewedFacult

Group-wise feature-based registration of CT and ultrasound images of spine.

Registration of pre-operative CT and freehand intra-operative ultrasound of lumbar spine could aid surgeons in the spinal needle injection which is a common procedure for pain management. Patients are always in a supine position during the CT scan, and in the prone or sitting position during the intervention. This leads to a difference in the spinal curvature between the two imaging modalities, which means a single rigid registration cannot be used for all of the lumbar vertebrae. In this work, a method for group-wise registration of pre-operative CT and intra-operative freehand 2-D ultrasound images of the lumbar spine is presented. The approach utilizes a pointbased registration technique based on the unscented Kalman filter, taking as input segmented vertebrae surfaces in both CT and ultrasound data. Ultrasound images are automatically segmented using a dynamic programming approach, while the CT images are semi-automatically segmented using thresholding. Since the curvature of the spine is different between the pre-operative and the intra-operative data, the registration approach is designed to simultaneously align individual groups of points segmented from each vertebra in the two imaging modalities. A biomechanical model is used to constrain the vertebrae transformation parameters during the registration and to ensure convergence. The mean target registration error achieved for individual vertebrae on five spine phantoms generated from CT data of patients, is 2.47 mm with standard deviation of 1.14 mm. Copyright 2010 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofReviewedFacult

Localization of pelvic anatomical coordinate system using atlas registration for total hip replacement, Medical Image Computing and Computer-Assisted Intervention 11

Abstract. In Total Hip Replacement (THR) procedures, misalignment of the acetabular component can lead to dislocation and impingement. For the successful alignment of acetabular component, precise estimation of pelvic anatomical coordinate system is necessary. Conventional navigation systems use CT scan or fluoroscopy, or involve implanted bone fiducials or invasive probing of bony landmarks to locate the anatomical coordinate. In this paper, an ultrasound-based approach is proposed that exploits prior knowledge about the anatomy of the pelvis in the form of a 3D surface atlas. Tracked ultrasound images are utilized to extract sample points from the surface of the pelvis. A generic coordinate system in the specific patient is localized by registering these points to a statistical atlas of the pelvis in which a canonical anatomical coordinate system had been defined. This technique has been evaluated using simulation, dry bone, and cadaver experiments and was able to localize the anatomical coordinate system with the accuracy of about 1 degree