Articulated Statistical Shape Model-Based 2D-3D Reconstruction of a Hip Joint

In this paper, reconstruction of three-dimensional (3D) patient-specific models of a hip joint from two-dimensional (2D) calibrated X-ray images is addressed. Existing 2D-3D reconstruction techniques usually reconstruct a patient-specific model of a single anatomical structure without considering the relationship to its neighboring structures. Thus, when those techniques would be applied to reconstruction of patient-specific models of a hip joint, the reconstructed models may penetrate each other due to narrowness of the hip joint space and hence do not represent a true hip joint of the patient. To address this problem we propose a novel 2D-3D reconstruction framework using an articulated statistical shape model (aSSM). Different from previous work on constructing an aSSM, where the joint posture is modeled as articulation in a training set via statistical analysis, here it is modeled as a parametrized rotation of the femur around the joint center. The exact rotation of the hip joint as well as the patient-specific models of the joint structures, i.e., the proximal femur and the pelvis, are then estimated by optimally fitting the aSSM to a limited number of calibrated X-ray images. Taking models segmented from CT data as the ground truth, we conducted validation experiments on both plastic and cadaveric bones. Qualitatively, the experimental results demonstrated that the proposed 2D-3D reconstruction framework preserved the hip joint structure and no model penetration was found. Quantitatively, average reconstruction errors of 1.9 mm and 1.1 mm were found for the pelvis and the proximal femur, respectively.

2D-3D Reconstruction-Based Planning of Total Hip Arthroplasty

This chapter proposed a personalized X-ray reconstruction-based planning and post-operative treatment evaluation framework called iJoint for advancing modern Total Hip Arthroplasty (THA). Based on a mobile X-ray image calibration phantom and a unique 2D-3D reconstruction technique, iJoint can generate patient-specific models of hip joint by non-rigidly matching statistical shape models to the X-ray radiographs. Such a reconstruction enables a true 3D planning and treatment evaluation of hip arthroplasty from just 2D X-ray radiographs whose acquisition is part of the standard diagnostic and treatment loop. As part of the system, a 3D model-based planning environment provides surgeons with hip arthroplasty related parameters such as implant type, size, position, offset and leg length equalization. With this newly developed system, we are able to provide true 3D solutions for computer assisted planning of THA using only 2D X-ray radiographs, which is not only innovative but also cost-effective.

A comparison between 2D and 3D cephalometry on CBCT scans of human skulls

The purpose of this study was to evaluate whether measurements on conventional cephalometric radiographs are comparable with 3D measurements on 3D models of human skulls, derived from cone beam CT (CBCT) data. A CBCT scan and a conventional cephalometric radiograph were made of 40 dry skulls. Standard cephalometric software was used to identify landmarks on both the 2D images and the 3D models. The same operator identified 17 landmarks on the cephalometric radiographs and on the 3D models. All images and 3D models were traced five times with a time-interval of 1 week and the mean value of repeated measurements was used for further statistical analysis. Distances and angles were calculated. Intra-observer reliability was good for all measurements. The reproducibility of the measurements on the conventional cephalometric radiographs was higher compared with the reproducibility of measurements on the 3D models. For a few measurements a clinically relevant difference between measurements on conventional cephalometric radiographs and 3D models was found. Measurements on conventional cephalometric radiographs can differ significantly from measurements on 3D models of the same skull. The authors recommend that 3D tracings for longitudinal research are not used in cases were there are only 2D records from the past.

Kernel density correlation based non-rigid point set matching for statistical model-based 2D/3D reconstruction

This paper presents a kernel density correlation based nonrigid point set matching method and shows its application in statistical model based 2D/3D reconstruction of a scaled, patient-specific model from an un-calibrated x-ray radiograph. In this method, both the reference point set and the floating point set are first represented using kernel density estimates. A correlation measure between these two kernel density estimates is then optimized to find a displacement field such that the floating point set is moved to the reference point set. Regularizations based on the overall deformation energy and the motion smoothness energy are used to constraint the displacement field for a robust point set matching. Incorporating this non-rigid point set matching method into a statistical model based 2D/3D reconstruction framework, we can reconstruct a scaled, patient-specific model from noisy edge points that are extracted directly from the x-ray radiograph by an edge detector. Our experiment conducted on datasets of two patients and six cadavers demonstrates a mean reconstruction error of 1.9 mm

Reconstruction and 3D visualisation based on objective real 3D based documentation

Reconstructions based directly upon forensic evidence alone are called primary information. Historically this consists of documentation of findings by verbal protocols, photographs and other visual means. Currently modern imaging techniques such as 3D surface scanning and radiological methods (Computer Tomography, Magnetic Resonance Imaging) are also applied. Secondary interpretation is based on facts and the examiner's experience. Usually such reconstructive expertises are given in written form, and are often enhanced by sketches. However, narrative interpretations can, especially in complex courses of action, be difficult to present and can be misunderstood. In this report we demonstrate the use of graphic reconstruction of secondary interpretation with supporting pictorial evidence, applying digital visualisation (using 'Poser') or scientific animation (using '3D Studio Max', 'Maya') and present methods of clearly distinguishing between factual documentation and examiners' interpretation based on three cases. The first case involved a pedestrian who was initially struck by a car on a motorway and was then run over by a second car. The second case involved a suicidal gunshot to the head with a rifle, in which the trigger was pushed with a rod. The third case dealt with a collision between two motorcycles. Pictorial reconstruction of the secondary interpretation of these cases has several advantages. The images enable an immediate overview, give rise to enhanced clarity, and compel the examiner to look at all details if he or she is to create a complete image.

3D Computerized Occlusion Rating of Embolized Experimental Aneurysms Using Noninvasive 1.5T MR Imaging

For embolized cerebral aneurysms, the initial occlusion rate is the most powerful parameter to predict aneurysm rerupture and recanalization. However, the occlusion rate is only estimated subjectively in clinical routine. To minimize subjective bias, computer occlusion-rating (COR) was successfully validated for 2D images. To minimize the remaining inaccuracy of 2D-COR, COR was applied to 1.5T 3D MR imaging.

Advanced morphological 3D magnetic resonance observation of cartilage repair tissue (MOCART) scoring using a new isotropic 3D proton-density, turbo spin echo sequence with variable flip angle distribution (PD-SPACE) compared to an isotropic 3D steady-state free precession sequence (True-FISP) and standard 2D sequences

To evaluate a new isotropic 3D proton-density, turbo-spin-echo sequence with variable flip-angle distribution (PD-SPACE) sequence compared to an isotropic 3D true-fast-imaging with steady-state-precession (True-FISP) sequence and 2D standard MR sequences with regard to the new 3D magnetic resonance observation of cartilage repair tissue (MOCART) score.