Can we improve the prediction of hip fracture by assessing bone structure using shape and appearance modelling?

Copyright 2013 Elsevier B.V., All rights reserved.Peer reviewedPreprin

The lumbar spine has an intrinsic shape specific to each individual that remains a characteristic throughout flexion and extension

Peer reviewedPostprin

Automatic Lumbar Vertebrae Segmentation in Fluoroscopic Images via Optimised Concurrent Hough Transform

Low back pain is a very common problem in the industrialised countries and its associated cost is enormous. Diagnosis of the underlying causes can be extremely difficult. Many studies have focused on mechanical disorders of the spine. Digital videofluoroscopy (DVF) was widely used to obtain images for motion studies. This can provide motion sequences of the lumbar spine, but the images obtained often suffer due to noise, exacerbated by the very low radiation dosage. Thus determining vertebrae position within the image sequence presents a considerable challenge. In this paper, we show how our new approach can automatically detect the positions and borders of vertebrae concurrently, relieving many of the problems experienced in other approaches. First, we use phase congruency to relieve difficulty associated with threshold selection in edge detection of the illumination variant DVF images. Then, our new Hough transform approach is applied to determine the moving vertebrae, concurrently. We include optimisation via a genetic algorithm as without it the extraction of moving multiple vertebrae is computationally daunting. Our results show that this new approach can indeed provide extractions of position and rotation which appear to be of sufficient quality to aid therapy and diagnosis of spinal disorders

Cube-Cut: Vertebral Body Segmentation in MRI-Data through Cubic-Shaped Divergences

In this article, we present a graph-based method using a cubic template for volumetric segmentation of vertebrae in magnetic resonance imaging (MRI) acquisitions. The user can define the degree of deviation from a regular cube via a smoothness value Delta. The Cube-Cut algorithm generates a directed graph with two terminal nodes (s-t-network), where the nodes of the graph correspond to a cubic-shaped subset of the image's voxels. The weightings of the graph's terminal edges, which connect every node with a virtual source s or a virtual sink t, represent the affinity of a voxel to the vertebra (source) and to the background (sink). Furthermore, a set of infinite weighted and non-terminal edges implements the smoothness term. After graph construction, a minimal s-t-cut is calculated within polynomial computation time, which splits the nodes into two disjoint units. Subsequently, the segmentation result is determined out of the source-set. A quantitative evaluation of a C++ implementation of the algorithm resulted in an average Dice Similarity Coefficient (DSC) of 81.33% and a running time of less than a minute.Comment: 23 figures, 2 tables, 43 references, PLoS ONE 9(4): e9338

Automated visual tracking for studying the ontogeny of zebrafish swimming

The zebrafish Danio rerio is a widely used model organism in studies of genetics, developmental biology, and recently, biomechanics. In order to quantify changes in swimming during all stages of development, we have developed a visual tracking system that estimates the posture of fish. Our current approach assumes planar motion of the fish, given image sequences taken from a top view. An accurate geometric fish model is automatically designed and fit to the images at each time frame. Our approach works across a range of fish shapes and sizes and is therefore well suited for studying the ontogeny of fish swimming, while also being robust to common environmental occlusions. Our current analysis focuses on measuring the influence of vertebra development on the swimming capabilities of zebrafish. We examine wild-type zebrafish and mutants with stiff vertebrae (stocksteif) and quantify their body kinematics as a function of their development from larvae to adult (mutants made available by the Hubrecht laboratory, The Netherlands). By tracking the fish, we are able to measure the curvature and net acceleration along the body that result from the fish's body wave. Here, we demonstrate the capabilities of the tracking system for the escape response of wild-type zebrafish and stocksteif mutant zebrafish. The response was filmed with a digital high-speed camera at 1500 frames s–1. Our approach enables biomechanists and ethologists to process much larger datasets than possible at present. Our automated tracking scheme can therefore accelerate insight in the swimming behavior of many species of (developing) fish

Tracking Lumbar Vertebrae in Digital Videofluoroscopic Video Automatically

Low back pain becomes one of the significant problem in the industrialized world. Efficient and effective spinal motion analysis is required to understand low back pain and to aid the diagnosis. Videofluoroscopy provides a cost effective way for such analysis. However, common approaches are tedious and time consuming due to the low quality of the images. Physicians have to extract the vertebrae manually in most cases and thus continuous motion analysis is hardly achieved. In this paper, we propose a system which can perform automatic vertebrae segmentation and tracking. Operators need to define exact location of landmarks in the first frame only. The proposed system will continuously learn the texture pattern along the edge and the dynamics of the vertebrae in the remaining frames. The system can estimate the location of the vertebrae based on the learnt texture and dynamics throughout the sequence. Experimental results show that the proposed system can segment vertebrae from videofluoroscopic images automatically and accurately. © Springer-Verlag 2004.postprintThe International Workshop on Medical Imaging and Augmented Reality (MIAR 2004), Beijing, China, 19-20 August 2004. In Lecture Notes in Computer Science, 2004, v. 3150, p. 154-16

Characterizing the shape of the lumbar spine using an active shape model: reliability and precision of the method

Copyright © 2008 Lippincott, Williams & WilkinsThis is a non-final version of an article published in final form in Spine Vol. 33 (7), pp. 807-813 (2008)Study Design. Analysis of positional magnetic resonance images of normal volunteers. Objective. To compare the reliability and precision of an active shape model to that of conventional lordosis measurements. Summary of Background Data. Characterization of lumbar lordosis commonly relies on measurement of angles; these have been found to have errors of around 10[degrees]. Methods. T2 weighted sagittal images of the lumbar spines of 24 male volunteers in the standing posture were acquired using a positional magnetic resonance scanner. An active shape model of the vertebral bodies from S1 to L1 was created. Lumbar lordosis was also determined by measuring the angles of the superior endplates. All measurements were performed twice by one observer and once by a second observer. Results. The shape model identified 2 modes of variation to describe the shape of the lumbar spine (mode 1 described curvature and mode 2 described evenness of curvature). Significant correlations were found between mode 1 and total lordosis (R = 0.97, P < 0.001) and between mode 2 and mean absolute deviation of segmental lordosis (R = 0.80, P < 0.001). Intra- and interobserver reliability was higher for the shape model (intraclass correlation coefficients, 0.98-1.00) than for the lordosis angle measurements (intraclass correlation coefficients, 0.68-0.99). The relative error of the shape model (mode 1 = 4%; mode 2 = 9%) was lower than the conventional measurements (total lordosis = 10%). Conclusion. The shape of the lumbar spine in the sagittal plane can be comprehensively characterized using a shape model. The results are more reliable and precise than measurements of lordosis calculated from endplate angles