A system for 3-D reconstruction of a patient-specific surface model from calibrated X-ray images

This paper presents a system for 3-D reconstruction of a patient-specific surface model from calibrated X-ray images. Our system requires two X-ray images of a patient with one acquired from the anterior-posterior direction and the other from the axial direction. A custom-designed cage is utilized in our system to calibrate both images. Starting from bone contours that are interactively identified from the X-ray images, our system constructs a patient-specific surface model of the proximal femur based on a statistical model based 2D/3D reconstruction algorithm. In this paper, we present the design and validation of the system with 25 bones. An average reconstruction error of 0.95 mm was observed.

Identification of erosional mechanisms during past glaciations based on a bedrock surface model of the central European Alps

The bedrock topography beneath the Quaternary cover provides an important archive for the identification of erosional processes during past glaciations. Here, we combined stratigraphic investigations of more than 40,000 boreholes with published data to generate a bedrock topography model for the entire plateau north of the Swiss Alps including the valleys within the mountain belt. We compared the bedrock map with data about the pattern of the erosional resistance of Alpine rocks to identify the controls of the lithologic architecture on the location of overdeepenings. We additionally used the bedrock topography map as a basis to calculate the erosional potential of the Alpine glaciers, which was related to the thickness of the LGM ice. We used these calculations to interpret how glaciers, with support by subglacial meltwater under pressure, might have shaped the bedrock topography of the Alps. We found that the erosional resistance of the bedrock lithology mainly explains where overdeepenings in the Alpine valleys and the plateau occur. In particular, in the Alpine valleys, the locations of overdeepenings largely overlap with areas where the underlying bedrock has a low erosional resistance, or where it was shattered by faults. We also found that the assignment of two end-member scenarios of erosion, related to glacial abrasion/plucking in the Alpine valleys, and dissection by subglacial meltwater in the plateau, may be adequate to explain the pattern of overdeepenings in the Alpine realm. This most likely points to the topographic controls on glacial scouring. In the Alps, the flow of LGM and previous glaciers were constrained by valley flanks, while ice flow was mostly divergent on the plateau where valley borders are absent. We suggest that these differences in landscape conditioning might have contributed to the contrasts in the formation of overdeepenings in the Alpine valleys and the plateau.

The role of upper-level dynamics and surface processes for the Pakistan flood of July 2010

In July and August 2010 floods of unprecedented impact afflicted Pakistan. The floods resulted from a series of intense multi-day precipitation events in July and early August. At the same time a series of blocking anticyclones dominated the upper-level flow over western Russia and breaking waves i.e. equatorward extrusions of stratospheric high potential vorticity (PV) air formed along the downstream flank of the blocks. Previous studies suggested that these extratropical upper-level breaking waves were crucial for instigating the precipitation events in Pakistan. Here a detailed analysis is provided of the extratropical forcing of the precipitation. Piecewise PV inversion is used to quantify the extratropical upper-level forcing associated with the wave breaking and trajectories are calculated to study the pathways and source regions of the moisture that precipitated over Pakistan. Limited-area model simulations are carried out to complement the Lagrangian analysis. The precipitation events over Pakistan resulted from a combination of favourable boundary conditions with strong extratropical and monsoonal forcing factors. Above-normal sea-surface temperatures in the Indian Ocean led to an elevated lower-tropospheric moisture content. Surface monsoonal depressions ensured the transport of moist air from the ocean towards northeastern Pakistan. Along this pathway the air parcel humidity increased substantially (60–90% of precipitated moisture) via evapotranspiration from the land surface. Extratropical breaking waves influenced the surface wind field substantially by enhancing the wind component directed towards the mountains which reinforced the precipitation.

Single fluoroscopic image based 2D/3D reconstruction of a scaled, patient-specific vertebral model

Purpose Accurate three-dimensional (3D) models of lumbar vertebrae can enable image-based 3D kinematic analysis. The common approach to derive 3D models is by direct segmentation of CT or MRI datasets. However, these have the disadvantages that they are expensive, timeconsuming and/or induce high-radiation doses to the patient. In this study, we present a technique to automatically reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image. Methods Our technique is based on a hybrid 2D/3D deformable registration strategy combining a landmark-to-ray registration with a statistical shape model-based 2D/3D reconstruction scheme. Fig. 1 shows different stages of the reconstruction process. Four cadaveric lumbar spine segments (total twelve lumbar vertebrae) were used to validate the technique. To evaluate the reconstruction accuracy, the surface models reconstructed from the lateral fluoroscopic images were compared to the associated ground truth data derived from a 3D CT-scan reconstruction technique. For each case, a surface-based matching was first used to recover the scale and the rigid transformation between the reconstructed surface model Results Our technique could successfully reconstruct 3D surface models of all twelve vertebrae. After recovering the scale and the rigid transformation between the reconstructed surface models and the ground truth models, the average error of the 2D/3D surface model reconstruction over the twelve lumbar vertebrae was found to be 1.0 mm. The errors of reconstructing surface models of all twelve vertebrae are shown in Fig. 2. It was found that the mean errors of the reconstructed surface models in comparison to their associated ground truths after iterative scaled rigid registrations ranged from 0.7 mm to 1.3 mm and the rootmean squared (RMS) errors ranged from 1.0 mm to 1.7 mm. The average mean reconstruction error was found to be 1.0 mm. Conclusion An accurate, scaled 3D reconstruction of the lumbar vertebra can be obtained from a single lateral fluoroscopic image using a statistical shape model based 2D/3D reconstruction technique. Future work will focus on applying the reconstructed model for 3D kinematic analysis of lumbar vertebrae, an extension of our previously-reported imagebased kinematic analysis. The developed method also has potential applications in surgical planning and navigation.

Validation of statistical shape model based reconstruction of the proximal femur - A morphology study

Seventeen bones (sixteen cadaveric bones and one plastic bone) were used to validate a method for reconstructing a surface model of the proximal femur from 2D X-ray radiographs and a statistical shape model that was constructed from thirty training surface models. Unlike previously introduced validation studies, where surface-based distance errors were used to evaluate the reconstruction accuracy, here we propose to use errors measured based on clinically relevant morphometric parameters. For this purpose, a program was developed to robustly extract those morphometric parameters from the thirty training surface models (training population), from the seventeen surface models reconstructed from X-ray radiographs, and from the seventeen ground truth surface models obtained either by a CT-scan reconstruction method or by a laser-scan reconstruction method. A statistical analysis was then performed to classify the seventeen test bones into two categories: normal cases and outliers. This classification step depends on the measured parameters of the particular test bone. In case all parameters of a test bone were covered by the training population's parameter ranges, this bone is classified as normal bone, otherwise as outlier bone. Our experimental results showed that statistically there was no significant difference between the morphometric parameters extracted from the reconstructed surface models of the normal cases and those extracted from the reconstructed surface models of the outliers. Therefore, our statistical shape model based reconstruction technique can be used to reconstruct not only the surface model of a normal bone but also that of an outlier bone.