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Minimally invasive and less invasive procedure is becoming more and more common in medical therapy. Image guidance is an indispensable component in minimally invasive procedures by providing critical information about the position...
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Minimally invasive and less invasive procedure is becoming more and more common in medical therapy. Image guidance is an indispensable component in minimally invasive procedures by providing critical information about the position of the target sites and the optimal manipulation of the devices, while the field of view is limited to naked eyes due to the small incision. Registration is one of the enabling technologies for computer-aided image guidance, which brings high-resolution pre-operative data into the operating room to provide more realistic information about the patient's anatomy. In this paper, we survey the recent advances in registration techniques applied to minimally and/or less invasive therapy, including a wide variety of therapies in surgery, endoscopy, interventional cardiology, interventional radiology, and hybrid procedures. The registration approaches are categorized into several groups, including projection-to-volume, slice-to-volume, video-to-volume, and volume-to-volume registration. The focus is on recent advances in registration techniques that are specifically developed for minimally and/or less invasive procedures in the following medical specialties: neuroradiology and neurosurgery, cardiac applications, and thoracic-abdominal interventions.
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Deformable image registration is a fundamental problem in computer vision and medical image computing. In this paper we investigate the use of graphical models in the context of a particular type of image registration problem, kno...
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Deformable image registration is a fundamental problem in computer vision and medical image computing. In this paper we investigate the use of graphical models in the context of a particular type of image registration problem, known as slice-to-volume registration. We introduce a scalable, modular and flexible formulation that can accommodate low-rank and high order terms, that simultaneously selects the plane and estimates the in-plane deformation through a single shot optimization approach. The proposed framework is instantiated into different variants seeking either a compromise between computational efficiency (soft plane selection constraints and approximate definition of the data similarity terms through pair-wise components) or exact definition of the data terms and the constraints on the plane selection. Simulated and real-data in the context of ultrasound and magnetic resonance registration (where both framework instantiations as well as different optimization strategies are considered) demonstrate the potentials of our method.
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Abstract Most motion correction methods work by aligning a set of volumes together, or to a volume that represents a reference location. These are based on an implicit assumption that the subject remains motionless during the seve...
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Abstract Most motion correction methods work by aligning a set of volumes together, or to a volume that represents a reference location. These are based on an implicit assumption that the subject remains motionless during the several seconds it takes to acquire all slices in a volume, and that any movement occurs in the brief moment between acquiring the last slice of one volume and the first slice of the next. This is clearly an approximation that can be more or less good depending on how long it takes to acquire one volume and in how rapidly the subject moves. In this paper we present a method that increases the temporal resolution of the motion correction by modelling movement as a piecewise continous function over time. This intra-volume movement correction is implemented within a previously presented framework that simultaneously estimates distortions, movement and movement-induced signal dropout. We validate the method on highly realistic simulated data containing all of these effects. It is demonstrated that we can estimate the true movement with high accuracy, and that scalar parameters derived from the data, such as fractional anisotropy, are estimated with greater fidelity when data has been corrected for intra-volume movement. Importantly, we also show that the difference in fidelity between data affected by different amounts of movement is much reduced when taking intra-volume movement into account. Additional validation was performed on data from a healthy volunteer scanned when lying still and when performing deliberate movements. We show an increased correspondence between the “still” and the “movement” data when the latter is corrected for intra-volume movement. Finally we demonstrate a big reduction in the telltale signs of intra-volume movement in data acquired on elderly subjects. Highlights ? We introduce a method to correct for intra-volume movement into an existing framework for movement and distortion correction. ? It has been validated on realistic simulated data and on experimental data with deliberate movement. ? The results indicate that one can reliably reverse the adverse effects of intra-volume movement.
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This paper addresses a registration refinement problem and presents an accurate and fast point-to-(tangmt) plane technique. Point-to-plane approach is known to be very accurate for registration refinement of partial 3D surfaces. H...
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This paper addresses a registration refinement problem and presents an accurate and fast point-to-(tangmt) plane technique. Point-to-plane approach is known to be very accurate for registration refinement of partial 3D surfaces. However, the computation complexity for finding the intersection point on a destination surface from a source control point is hindering the algorithm from real-time applications. We introduce a novel point-to-plane registration technique by combining the high-speed advantage of point-to-projection technique. In order to find the intersection point fast and accurately, we forward-project the source point to the destination surface and reproject the projection point to the normal vector of the source point. We show that iterative projections of the projected destination point to the normal vector converge to the intersection point. By assuming the destination surface to be a monotonic function in a new 2D coordinate system, we show contraction mapping properties of our iterative projection technique. Experimental results for several objects are presented for both pair-wise and multi-view registrations.
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During the last decades, the research community of medical imaging has witnessed continuous advances in image registration methods, which pushed the limits of the state-of-the-art and enabled the development of novel medical proce...
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During the last decades, the research community of medical imaging has witnessed continuous advances in image registration methods, which pushed the limits of the state-of-the-art and enabled the development of novel medical procedures. A particular type of image registration problem, known as slice-to-volume registration, played a fundamental role in areas like image guided surgeries and volumetric image reconstruction. However, to date, and despite the extensive literature available on this topic, no survey has been written to discuss this challenging problem. This paper introduces the first comprehensive survey of the literature about slice-to-volume registration, presenting a categorical study of the algorithms according to an ad-hoc taxonomy and analyzing advantages and disadvantages of every category. We draw some general conclusions from this analysis and present our perspectives on the future of the field. (C) 2017 Elsevier B.V. All rights reserved.
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MiniMCA (Miniature Multiple Camera Array) is a lightweight, frame-based, and multilens composed multispectral sensor, which is suitable to mount on an unmanned aerial systems (UAS) to acquire high spatial and temporal resolution i...
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MiniMCA (Miniature Multiple Camera Array) is a lightweight, frame-based, and multilens composed multispectral sensor, which is suitable to mount on an unmanned aerial systems (UAS) to acquire high spatial and temporal resolution imagery for various remote sensing applications. Since MiniMCA has significant band misregistration effect, an automatic and precise band-to-band registration (BBR) method is proposed in this study. Based on the principle of sensor plane-to-plane projection, a modified projective transformation (MPT) model is developed. It is to estimate all coefficients of MPT from indoor camera calibration, together with two systematic errors correction. Therefore, we can transfer all bands into the same image space. Quantitative error analysis shows that the proposed BBR scheme is scene independent and can achieve 0.33 pixels of accuracy, which demonstrating the proposed method is accurate and reliable. Meanwhile, it is difficult to mark ground control points (GCPs) on the MiniMCA images, as its spatial resolution is low when the flight height is higher than 400 m. In this study, a higher resolution RGB camera is adopted to produce digital surface model (DSM) and assist MiniMCA ortho-image generation. After precise BBR, only one reference band of MiniMCA image is necessary for aerial triangulation because all bands have same exterior and interior orientation parameters. It means that all the MiniMCA imagery can be ortho-rectified through the same exterior and interior orientation parameters of the reference band. The result of the proposed ortho-rectification procedure shows the co-registration errors between MiniMCA reference band and the RGB ortho-images is less than 0.6 pixels. (C) 2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
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Purpose: This study developed and assessed a slice-to-volume registration method that integrated three-dimensional (3D) static MRI volumes of the bones with a novel single-slice, real-time radial fast low-angle shot MRI for measur...
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Purpose: This study developed and assessed a slice-to-volume registration method that integrated three-dimensional (3D) static MRI volumes of the bones with a novel single-slice, real-time radial fast low-angle shot MRI for measuring the 3D kinematics of the knee. Methods: Multislice 3D images (for establishing bone models) and 2D real-time images of the knee at five static positions, and 2D real-time images of the knee during flexion/extension were acquired from three healthy adults. The 3D bone poses, and thus the 3D kinematics of the knee, were obtained by registering the real-time images to a reformed slice interpolated from the bone models according to the WEMS similarity measure. The ensemble means (biases) and standard deviations (precisions) of the measurement errors of the proposed measurement method, i.e., differences between the 3D images and the registered poses, were calculated across all the static trials of all subjects. Ensemble standard deviations of all the repeated registrations for the dynamic data of all subjects were obtained to indicate the repeatability of the registration method. Results: The ensemble means (standard deviations) of the measurement errors of the femoral poses were less than 0.6 (0.6) mm for translations and -0.2° (1.3°) degrees for rotations. The corresponding values for the tibia were 0.5 (0.7) mm and -0.4° (1.1°), respectively. The ensemble means (standard deviations) of the measurement errors of knee joint poses were less than 0.9 (1.4) mm for translations and -0.3° (1.8°) degrees for rotations. For registration repeatability of dynamic tests, the ensemble standard deviations were all less than 1.2 mm for translations and 1.5° for rotations. Conclusions: With the accuracy and repeatability achieved, and without the use of ionizing radiation and multiple repetitive motions, the proposed method combining the novel real-time MR imaging promises to be a valuable tool for studying 3D knee kinematics noninvasively.
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This paper introduces a novel decomposed graphical model to deal with slice-to-volume registration in the context of medical images and image-guided surgeries.
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In this paper, we describe a method of automatic 3D-2D projective registration between the 3D (i.e. polygonal face surface derived from CT or MRI data) and the 2D faces of the same individual in the photographs. Our task is to mak...
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In this paper, we describe a method of automatic 3D-2D projective registration between the 3D (i.e. polygonal face surface derived from CT or MRI data) and the 2D faces of the same individual in the photographs. Our task is to make a realistic 3D model face for post-surgical simulation by pasting color textures accurately on the face surface. We utilize edge features such as external edge (facial outline) and internal edges like eye, nose and mouth edges from both the 3D face and photographs for matching. We define 3D edge as a set of 3D surface points which is 2D edge on the projected space.
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Background and Objective: Liver tumor ablation is often guided by ultrasound (US). Due to poor image quality, intraoperative US is fused with preoperative computed tomography or magnetic tomography (CT/MR) images to provide visual...
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Background and Objective: Liver tumor ablation is often guided by ultrasound (US). Due to poor image quality, intraoperative US is fused with preoperative computed tomography or magnetic tomography (CT/MR) images to provide visual guidance. As of today, the underlying 2D US to 3D CT/MR registration problem remains a very challenging task.
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