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Unsupervised Detection of Disturbances in 2D Radiographs

We present a method based on a generative model for detection of disturbances such as prosthesis, screws, zippers, and metals in 2D radiographs. The generative model is trained in an unsupervised fashion using clinical radiographs as well as …

Automatic Vessel Segmentation and Aneurysm Detection Pipeline for Numerical Fluid Analysis

Computational Fluid Dynamic calculations are a great assistance for rupture prediction of cerebral aneurysms. This procedure requires a consistent surface, as well as a separation of the blood vessel and aneurysm on this surface to calculate …

Automated Virtual Reconstruction of Large Skull Defects Using Statistical Shape Models and Generative Adversarial Networks

We present an automated method for extrapolating missing regions in label data of the skull in an anatomically plausible manner. The ultimate goal is to design patient-specific cranial implants for correcting large, arbitrarily shaped defects of the …

Unsupervised Learning and Statistical Shape Modeling of the Morphometry and Hemodynamics of Coarctation of the Aorta

Image-based patient-specific modeling of blood flow is a current state of the art approach in cardiovascular research proposed to support diagnosis and treatment decision. However, the approach is time-consuming, and the absence of large data sets …

Automatic Quantification of Hip Osteoarthritis From Low Quality X-Ray Images

Diagnosis of hip osteoarthritis is conventionally done through a manual measurement of the joint distance between the femoral head and the acetabular cup, a difficult and often error-prone process. Recently, Chen et al. proposed a fully automated …

Aortic Shape Synthesiser - Understanding Anatomical Variations of the Thoracic Aorta

Population-based models of morphological variability are useful for automating medical image processing tasks, diagnosis, device and tool design, education and training as well as exploratory hypothesis formation in clinical research. We present a …

Validation of a Statistical Shape Model for Acetabular Bone Defect Analysis

Acetabular bone defects are still challenging to quantify. Numerous classification schemes have been proposed to categorize the diverse kinds of defects. However, these classification schemes are mainly descriptive and hence it remains difficult to …

3D Shape Analysis for Coarctation of the Aorta

A population of 54 cases diagnosed with coarctation of the aorta (CoA) was investigated for correlations between complex 3D shape and clinical parameters. Based on a statistical shape model (SSM) of the aortic arch (AA) including supra-aortic …

Evaluating two Methods for Geometry Reconstruction from Sparse Surgical Navigation Data

In this study we investigate methods for fitting a Statistical Shape Model (SSM) to intra-operatively acquired point cloud data from a surgical navigation system. We validate the fitted models against the pre-operatively acquired Magnetic Resonance …

Robust and Accurate Appearance Models Based on Joint Dictionary Learning: Data From the Osteoarthritis Initiative

Deformable model-based approaches to 3D image segmentation have been shown to be highly successful. Such methodology requires an appearance model that drives the deformation of a geometric model to the image data. Appearance models are usually either …