Stuart Crozier

University of Queensland, Brisbane, Queensland, Australia

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Publications (451)558.88 Total impact

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    ABSTRACT: Recent studies have consistently shown that amongst staff working with MRI, transient symptoms directly attributable to the MRI system including dizziness, nausea, tinnitus, and concentration problems are reported. This study assessed symptom prevalence and incidence in radiographers and other staff working with MRI in healthcare in the UK. One hundred and four volunteer staff from eight sites completed a questionnaire and kept a diary to obtain information on subjective symptoms and work practices, and wore a magnetic field dosimeter during one to three randomly selected working days. Incidence of MRI-related symptoms was obtained for all shifts and prevalence of MRI-related and reference symptoms was associated to explanatory factors using ordinal regression. Incident symptoms related to working with MRI were reported in 4 % of shifts. Prevalence of MRI-related, but not reference symptoms were associated with number of hours per week working with MRI, shift length, and stress, but not with magnetic field strength (1.5 and 3 T) or measured magnetic field exposure. Reporting of prevalent symptoms was associated with longer duration of working in MRI departments, but not with measured field strength of exposure. Other factors related to organisation and stress seem to contribute to increased reporting of MRI-related symptoms. • Routine work with MRI is associated with increased reporting of transient symptoms • No link to the strength of the magnetic field was demonstrated. • Organisational factors and stress additionally contribute to reporting of MRI-related symptoms.
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    ABSTRACT: PurposeTo validate a fully automated scheme to extract biochemical information from the hip joint cartilages using MR T2 mapping images incorporating segmentation of co-registered three-dimensional Fast-Spin-Echo (3D-SPACE) images.Methods Manual analyses of unilateral hip (3 Tesla) MR images of 24 asymptomatic volunteers were used to validate a 3D deformable model method for automated cartilage segmentation of SPACE scans, partitioning of the individual femoral and acetabular cartilage plates into clinically defined sub-regions and propagating these results to T2 maps to calculate region-wise T2 value statistics. Analyses were completed on a desktop computer (∼10 min per case).ResultsThe mean voxel overlap between automated A and manual M segmentations of the cartilage volumes in the (clinically based) SPACE images was 73% . The automated and manual analyses demonstrated a relative difference error <10% in the median “T2 average signal” for each cartilage plate. The automated and manual analyses showed consistent patterns between significant differences in T2 data across the hip cartilage sub-regions.Conclusion The good agreement between the manual and automatic analyses of T2 values indicates the use of structural 3D-SPACE MR images with the proposed method provides a promising approach for automated quantitative T2 assessment of hip joint cartilages. Magn Reson Med, 2015. © 2015 Wiley Periodicals, Inc.
    Magnetic Resonance in Medicine 01/2015; DOI:10.1002/mrm.25598 · 3.40 Impact Factor
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    ABSTRACT: We present a statistical shape model approach for automated segmentation of the proximal humerus and scapula with subsequent bone-cartilage interface (BCI) extraction from 3D magnetic resonance (MR) images of the shoulder region. Manual and automated bone segmentations from shoulder MR examinations from 25 healthy subjects acquired using steady-state free precession sequences were compared with the Dice similarity coefficient (DSC). The mean DSC scores between the manual and automated segmentations of the humerus and scapula bone volumes surrounding the BCI region were 0.926 ± 0.050 and 0.837 ± 0.059, respectively. The mean DSC values obtained for BCI extraction were 0.806 ± 0.133 for the humerus and 0.795 ± 0.117 for the scapula. The current model-based approach successfully provided automated bone segmentation and BCI extraction from MR images of the shoulder. In future work, this framework appears to provide a promising avenue for automated segmentation and quantitative analysis of cartilage in the glenohumeral joint.
    Physics in Medicine and Biology 01/2015; 60(4):1441-1459. DOI:10.1088/0031-9155/60/4/1441 · 2.92 Impact Factor
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    ABSTRACT: Using a new rotating SENSitivity Encoding (rotating-SENSE) algorithm, we have successfully demonstrated that the rotating radiofrequency coil array (RRFCA) is capable of achieving a significant reduction in scan time and a uniform image reconstruction for a homogeneous phantom at 7 Tesla. However, at 7 Tesla the in vivo sensitivity profiles ( ) become distinct at various angular positions. Therefore, sensitivity at other angular positions cannot be obtained by numerically rotating the acquired sensitivity. In this work, a novel sensitivity estimation method for the RRFCA was developed and validated with in vivo human brain imaging. The method employed a library database and registration techniques to estimate coil sensitivity at an arbitrary angular position. The estimated sensitivity maps were then compared to the acquired sensitivity maps. The results indicate that the proposed method is capable of accurately estimating both the magnitude and phase of the sensitivity maps at an arbitrary angular position, which enables us to employ the rotating-SENSE method to perform acceleration and image reconstruction. Compared to a stationary coil array with the same number of coil elements, the RRFCA was able to reconstruct good quality images at a high reduction factor. It is hoped that the proposed sensitivity estimation algorithm and the acceleration ability of the RRFCA will be particularly useful for ultra high field MRI.
    Journal of Magnetic Resonance 12/2014; 252C. DOI:10.1016/j.jmr.2014.12.004 · 2.32 Impact Factor
  • Jin Jin, Feng Liu, Stuart Crozier
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    ABSTRACT: It is generally a challenging task to reconstruct dynamic magnetic resonance (MR) images with high spatial and high temporal resolutions, especially with highly incomplete k-space sampling. In this work, a novel method that combines a non-rigid image registration technique with sparsity-constrained image reconstruction is introduced. Employing a multi-resolution free-form deformation technique with B-spline interpolations, the non-rigid image registration accurately models the complex deformations of the physiological dynamics, and provides artefact-suppressed high spatial-resolution predictions. Based on these prediction images, the sparsity-constrained data fidelity-enforced image reconstruction further improves the reconstruction accuracy. When compared with the k-t FOCUSS with motion estimation/motion compensation (MEMC) technique on volunteer scans, the proposed method consistently outperforms in both the spatial and the temporal accuracy with variously accelerated k-space sampling. High fidelity reconstructions for dynamic systolic phases with reduction factor of 10 and cardiac perfusion series with reduction factor of 3 are presented.
    Magnetic Resonance Imaging 12/2014; 32(10). DOI:10.1016/j.mri.2014.08.006 · 2.02 Impact Factor
  • HortScience: a publication of the American Society for Horticultural Science 11/2014; 32:112-113. · 0.86 Impact Factor
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    ABSTRACT: Accurate segmentation of hip joint cartilage from magnetic resonance (MR) images offers opportunities for quantitative investigations of pathoanatomical conditions such as osteoarthritis. In this paper, we present a fully automatic scheme for the segmentation of the individual femoral and acetabular cartilage plates in the human hip joint from high-resolution 3D MR images. The developed scheme uses an improved optimal multi-object multi-surface graph search framework with an arc-weighted graph representation that incorporates prior morphological knowledge as a basis for segmentation of the individual femoral and acetabular cartilage plates despite weak or incomplete boundary interfaces. This automated scheme was validated against manual segmentations from 3D true fast imaging with steady-state precession (TrueFISP) MR examinations of the right hip joints in 52 asymptomatic volunteers. Compared with expert manual segmentations of the combined, femoral and acetabular cartilage volumes, the automatic scheme obtained mean (± standard deviation) Dice's similarity coefficients of 0.81 (± 0.03), 0.79 (± 0.03) and 0.72 (± 0.05). The corresponding mean absolute volume difference errors were 8.44% (± 6.36), 9.44% (± 7.19) and 9.05% (± 8.02). The mean absolute differences between manual and automated measures of cartilage thickness for femoral and acetabular cartilage plates were 0.13 mm (± 0.12) and 0.11 mm (± 0.11), respectively.
    Physics in Medicine and Biology 11/2014; 59(23):7245-7266. DOI:10.1088/0031-9155/59/23/7245 · 2.92 Impact Factor
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    ABSTRACT: l1-SPIRiT is a fast magnetic resonance imaging (MRI) method which combines parallel imaging (PI) with compressed sensing (CS) by performing a joint l1-norm and l2-norm optimization procedure. The original l1-SPIRiT method uses two-dimensional (2D) Wavelet transform to exploit the intra-coil data redundancies and a joint sparsity model to exploit the inter-coil data redundancies. In this work, we propose to stack all the coil images into a three-dimensional (3D) matrix, and then a novel 3D Walsh transform-based sparsity basis is applied to simultaneously reduce the intra-coil and inter-coil data redundancies. Both the 2D Wavelet transform-based and the proposed 3D Walsh transform-based sparsity bases were investigated in the l1-SPIRiT method. The experimental results show that the proposed 3D Walsh transform-based l1-SPIRiT method outperformed the original l1-SPIRiT in terms of image quality and computational efficiency.
    Magnetic Resonance Imaging 09/2014; 32(7). DOI:10.1016/j.mri.2014.04.008 · 2.02 Impact Factor
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    ABSTRACT: Objective To validate an automatic scheme for the segmentation and quantitative analysis of the medial (MM) and lateral meniscus (LM) in magnetic resonance (MR) images of the knee. Method We analysed sagittal water-excited dual-echo steady-state MR images of the knee from a subset of the Osteoarthritis Initiative cohort. The MM and LM were automatically segmented in the MR images based on a deformable model approach. Quantitative parameters including volume, subluxation and tibial-coverage were automatically calculated for comparison (Wilcoxon tests) between knees with variable radiographic osteoarthritis (rOA), medial and lateral joint space narrowing (mJSN, lJSN) and pain. Automatic segmentations and estimated parameters were evaluated for accuracy using manual delineations of the menisci in 88 pathological knee MR examinations at baseline and 12 months time-points. Results The median (95% confidence-interval) Dice similarity index ( 2*|Auto ∩Manual|/(|Auto|+|Manual|)*100 2*|Auto∩ Manual|/(|Auto|+|Manual|)*100) between manual and automated segmentations for the MM and LM were 78.3%(75.0—78.7), 83.9%(82.1—83.9) at baseline and 75.3%(72.8—76.9), 83.0%(81.6—83.5) at 12 months. Pearson coefficients between automatic and manual segmentation parameters ranged from r=0.70 to r=0.92. MM in rOA/mJSN knees had significantly greater subluxation and smaller tibial-coverage than no-rOA/no-mJSN knees. LM in rOA knees had significantly greater volumes and tibial-coverage than no-rOA knees. Conclusion Our automated method successfully segmented the menisci in normal and osteoarthritic knee MR images and detected meaningful morphological differences with respect to rOA and JSN. Our approach will facilitate analyses of the menisci in prospective MR cohorts such as the OAI for investigations into pathophysiological changes occurring in early OA development.
    Osteoarthritis and Cartilage 09/2014; 22(9). DOI:10.1016/j.joca.2014.06.029 · 4.66 Impact Factor
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    ABSTRACT: Clinical and research staff who work around magnetic resonance imaging (MRI) scanners are exposed to the static magnetic stray fields of these scanners. Although the past decade has seen strong developments in the assessment of occupational exposure to electromagnetic fields from MRI scanners, there is insufficient insight into the exposure variability that characterizes routine MRI work practice. However, this is an essential component of risk assessment and epidemiological studies. This paper describes the results of a measurement survey of shift-based personal exposure to static magnetic fields (SMF) (B) and motion-induced time-varying magnetic fields (dB/dt) among workers at 15 MRI facilities in the Netherlands. With the use of portable magnetic field dosimeters, >400 full-shift and partial shift exposure measurements were collected among various jobs involved in clinical and research MRI. Various full-shift exposure metrics for B and motion-induced dB/dt exposure were calculated from the measurements, including instantaneous peak exposure and time-weighted average (TWA) exposures. We found strong correlations between levels of static (B) and time-varying (dB/dt) exposure (r = 0.88-0.92) and between different metrics (i.e. peak exposure, TWA exposure) to express full-shift exposure (r = 0.69-0.78). On average, participants were exposed to MRI-related SMFs during only 3.7% of their work shift. Average and peak B and dB/dt exposure levels during the work inside the MRI scanner room were highest among technical staff, research staff, and radiographers. Average and peak B exposure levels were lowest among cleaners, while dB/dt levels were lowest among anaesthesiology staff. Although modest exposure variability between workplaces and occupations was observed, variation between individuals of the same occupation was substantial, especially among research staff. This relatively large variability between workers with the same job suggests that exposure classification based solely on job title may not be an optimal grouping strategy for epidemiological purposes.
    Annals of Occupational Hygiene 08/2014; DOI:10.1093/annhyg/meu057 · 2.07 Impact Factor
  • Yang Yang, Feng Liu, Wenlong Xu, Stuart Crozier
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    ABSTRACT: Compressed sensing has been applied to magnetic resonance imaging (MRI) for the acceleration of data collection. However, existing compressed sensing (CS) techniques usually produce images with residual artifacts, particularly at high reduction factors. In this work, we propose a novel, two-stage reconstruction scheme, which takes advantage of the properties of k-space data and under-sampling patterns that are useful in CS. In this algorithm, the under-sampled k-space data is segmented into low-frequency and high-frequency domains. Then, in stage one, using dense measurements, the low-frequency region of k-space data is faithfully reconstructed. The fully reconstituted low-frequency k-space data from the first stage is then combined with the high-frequency k-space data to complete the second stage reconstruction of the whole of k-space. With this two-stage approach, each reconstruction inherently incorporates a lower data under-sampling rate and more homogeneous signal magnitudes than conventional approaches. Because the restricted isometric property is easier to satisfy, the reconstruction consequently produces lower residual errors at each step. Compared with a conventional CS reconstruction, for the cases of cardiac cine, sagittal brain MR and angiogram imaging, the proposed method achieves a more accurate reconstruction with an improvement of 2 ~ 4dB in peak signal-to-noise ratio respectively, using reduction factors of up to 6.
    IEEE transactions on bio-medical engineering 07/2014; 62(1). DOI:10.1109/TBME.2014.2341621 · 2.15 Impact Factor
  • Paul J. Keall, Michael Barton, Stuart Crozier
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    ABSTRACT: The Australian magnetic resonance imaging (MRI)–Linac program is a $16-million government-funded project to advance the science and clinical practice of exquisite real-time anatomical and physiological adaptive cancer therapy. The centerpiece of the program is a specifically designed 1-T open-bore MRI/6-MV linac system that is planned for delivery and completion of installation in 2014. Current scientific endeavors include engineering discovery in MRI component design, quantifying MRI and linac interactions, and developing image guidance and adaptation strategies.
    Seminars in radiation oncology 07/2014; 24(3):203–206. DOI:10.1016/j.semradonc.2014.02.015 · 3.77 Impact Factor
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    ABSTRACT: Magnetic resonance (MR) examinations of morphological characteristics of intervertebral discs (IVDs) have been used extensively for biomechanical studies and clinical investigations of the lumbar spine. Traditionally, the morphological measurements have been performed using time- and expertise-intensive manual segmentation techniques not well suited for analyses of large-scale studies.
    The spine journal: official journal of the North American Spine Society 06/2014; 14(11). DOI:10.1016/j.spinee.2014.05.023 · 2.90 Impact Factor
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    Yeyang Yu, Jin Jin, Feng Liu, Stuart Crozier
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    ABSTRACT: Compressed Sensing (CS) has been applied in dynamic Magnetic Resonance Imaging (MRI) to accelerate the data acquisition without noticeably degrading the spatial-temporal resolution. A suitable sparsity basis is one of the key components to successful CS applications. Conventionally, a multidimensional dataset in dynamic MRI is treated as a series of two-dimensional matrices, and then various matrix/vector transforms are used to explore the image sparsity. Traditional methods typically sparsify the spatial and temporal information independently. In this work, we propose a novel concept of tensor sparsity for the application of CS in dynamic MRI, and present the Higher-order Singular Value Decomposition (HOSVD) as a practical example. Applications presented in the three- and four-dimensional MRI data demonstrate that HOSVD simultaneously exploited the correlations within spatial and temporal dimensions. Validations based on cardiac datasets indicate that the proposed method achieved comparable reconstruction accuracy with the low-rank matrix recovery methods and, outperformed the conventional sparse recovery methods.
    PLoS ONE 06/2014; 9(6):e98441. DOI:10.1371/journal.pone.0098441 · 3.53 Impact Factor
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    ABSTRACT: A potential side effect of inline MRI-linac systems is electron contamination focusing causing a high skin dose. In this work, the authors reexamine this prediction for an open bore 1 T MRI system being constructed for the Australian MRI-Linac Program. The efficiency of an electron contamination deflector (ECD) in purging electron contamination from the linac head is modeled, as well as the impact of a helium gas region between the deflector and phantom surface for lowering the amount of air-generated contamination. Magnetic modeling of the 1 T MRI was used to generate 3D magnetic field maps both with and without the presence of an ECD located immediately below the MLC's. Forty-seven different ECD designs were modeled and for each the magnetic field map was imported into Geant4 Monte Carlo simulations including the linac head, ECD, and a 30 × 30 × 30 cm(3) water phantom located at isocenter. For the first generation system, the x-ray source to isocenter distance (SID) will be 160 cm, resulting in an 81.2 cm long air gap from the base of the ECD to the phantom surface. The first 71.2 cm was modeled as air or helium gas, with the latter encased between two windows of 50 μm thick high density polyethlyene. 2D skin doses (at 70 μm depth) were calculated across the phantom surface at 1 × 1 mm(2) resolution for 6 MV beams of field size of 5 × 5, 10 × 10, and 20 × 20 cm(2). The skin dose was predicted to be of similar magnitude as the generic systems modeled in previous work, 230% to 1400% of[Formula: see text] for 5 × 5 to 20 × 20 cm(2), respectively. Inclusion of the ECD introduced a nonuniformity to the MRI imaging field that ranged from ∼20 to ∼140 ppm while the net force acting on the ECD ranged from ∼151 N to ∼1773 N. Various ECD designs were 100% efficient at purging the electron contamination into the ECD magnet banks; however, a small percentage were scattered back into the beam and continued to the phantom surface. Replacing a large portion of the extended air-column between the ECD and phantom surface with helium gas is a key element as it significantly minimized the air-generated contamination. When using an optimal ECD and helium gas region, the 70 μm skin dose is predicted to increase moderately inside a small hot spot over that of the case with no magnetic field present for the jaw defined square beams examined here. These increases include from 12% to 40% of [Formula: see text] for 5 × 5 cm(2), 18% to 55% of [Formula: see text] for 10 × 10 cm(2), and from 23% to 65% of [Formula: see text] for 20 × 20 cm(2). Coupling an efficient ECD and helium gas region below the MLCs in the 160 cm isocenter MRI-linac system is predicted to ameliorate the impact electron contamination focusing has on skin dose increases. An ECD is practical as its impact on the MRI imaging distortion is correctable, and the mechanical forces acting on it manageable from an engineering point of view.
    Medical Physics 05/2014; 41(5):051708. DOI:10.1118/1.4871618 · 3.01 Impact Factor
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    ABSTRACT: PurposeTo present and evaluate a fully automatic method for segmentation (i.e., detection and delineation) of suspicious tissue in breast MRI.Materials and Methods The method, based on mean-shift clustering and graph-cuts on a region adjacency graph, was developed and its parameters tuned using multimodal (T1, T2, DCE-MRI) clinical breast MRI data from 35 subjects (training data). It was then tested using two data sets. Test set 1 comprises data for 85 subjects (93 lesions) acquired using the same protocol and scanner system used to acquire the training data. Test set 2 comprises data for eight subjects (nine lesions) acquired using a similar protocol but a different vendor's scanner system. Each lesion was manually delineated in three-dimensions by an experienced breast radiographer to establish segmentation ground truth. The regions of interest identified by the method were compared with the ground truth and the detection and delineation accuracies quantitatively evaluated.ResultsOne hundred percent of the lesions were detected with a mean of 4.5 ± 1.2 false positives per subject. This false-positive rate is nearly 50% better than previously reported for a fully automatic breast lesion detection system. The median Dice coefficient for Test set 1 was 0.76 (interquartile range, 0.17), and 0.75 (interquartile range, 0.16) for Test set 2.Conclusion The results demonstrate the efficacy and accuracy of the proposed method as well as its potential for direct application across different MRI systems. It is (to the authors' knowledge) the first fully automatic method for breast lesion detection and delineation in breast MRI. J. Magn. Reson. Imaging 2014;39:795–804. © 2013 Wiley Periodicals, Inc.
    Journal of Magnetic Resonance Imaging 04/2014; 39(4). DOI:10.1002/jmri.24229 · 2.57 Impact Factor
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    ABSTRACT: In this study, the effects of cardiac fibroblast proliferation on cardiac electric excitation conduction and mechanical contraction were investigated using a proposed integrated myocardial-fibroblastic electromechanical model. At the cellular level, models of the human ventricular myocyte and fibroblast were modified to incorporate a model of cardiac mechanical contraction and cooperativity mechanisms. Cellular electromechanical coupling was realized with a calcium buffer. At the tissue level, electrical excitation conduction was coupled to an elastic mechanics model in which the finite difference method (FDM) was used to solve electrical excitation equations, and the finite element method (FEM) was used to solve mechanics equations. The electromechanical properties of the proposed integrated model were investigated in one or two dimensions under normal and ischemic pathological conditions. Fibroblast proliferation slowed wave propagation, induced a conduction block, decreased strains in the fibroblast proliferous tissue, and increased dispersions in depolarization, repolarization, and action potential duration (APD). It also distorted the wave-front, leading to the initiation and maintenance of re-entry, and resulted in a sustained contraction in the proliferous areas. This study demonstrated the important role that fibroblast proliferation plays in modulating cardiac electromechanical behaviour and which should be considered in planning future heart-modeling studies.
    Journal of Zhejiang University SCIENCE B 03/2014; 15(3):225-42. DOI:10.1631/jzus.B1300156 · 1.11 Impact Factor
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    ABSTRACT: Despite radical treatment with surgery, radiotherapy and chemotherapy, advanced gliomas recur within months. Geographic misses in radiotherapy planning may play a role in this seemingly ineluctable recurrence. Planning is typically performed on post-contrast MRIs, which are known to underreport tumour volume relative to FDOPA PET scans. FDOPA PET fused with contrast enhanced MRI has demonstrated greater sensitivity and specificity than MRI alone. One sign of potential misses would be differences between gross target volumes (GTVs) defined using MRI alone and when fused with PET. This work examined whether such a discrepancy may occur. Materials and Methods: For six patients, a 75 minute PET scan using 3,4-dihydroxy-6-18F-fluoro-L-phynel-alanine (18F-FDOPA) was taken within 2 days of gadolinium enhanced MRI scans. In addition to standard radiotherapy planning by an experienced radiotherapy oncologist, a second gross target volume (GTV) was defined by an experienced nuclear medicine specialist for fused PET and MRI, while blinded to the radiotherapy plans. The volumes from standard radiotherapy planning were compared to the PET defined GTV. Results: The comparison indicated radiotherapy planning would change in several cases if FDOPA PET data was available. PET-defined contours were external to 95% prescribed dose for several patients. However, due to the radiotherapy margins, the discrepancies were relatively small in size and all received a dose of 50 Gray or more. Conclusions: Given the limited size of the discrepancies it is uncertain that geographic misses played a major role in patient outcome. Even so, the existence of discrepancies indicates that FDOPA PET could assist in better defining margins when planning radiotherapy for advanced glioma, which could be important for highly conformal radiotherapy plans.
    Journal of Physics Conference Series 02/2014; 489(1). DOI:10.1088/1742-6596/489/1/012028
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    ABSTRACT: Tumours are known to be heterogeneous, yet typical treatment plans consider them as a single unit. This may influence treatment outcomes. However, treatment cannot be customised to intra-tumour variation without a method to establish outcomes at an intra-tumour scale. This work proposes a method to both assess and measure outcomes locally within tumours. Methods: Four patients were scanned at two post-surgery time points using contrast enhanced MRI and 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (18F-DOPA) PET. The shell of active tumour tissue is divided into a set of small subregions at both time points. Local outcome is measured from changes in subregion volume over time. The utility of the proposed approach is evaluated by measuring the correlation between PET uptake and documented growth. Correlation with overall survival time was also examined. Results: Local outcomes were heterogeneous and evidence of a positive correlation between local 18F-DOPA uptake and local progression was observed. Conclusions: Given that intra-tumour outcomes are heterogeneous the consistently positive correlation between FDOPA uptake and progression, local analysis of tumours could prove useful for treatment planning.
    Journal of Physics Conference Series 02/2014; 489(1). DOI:10.1088/1742-6596/489/1/012073
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    ABSTRACT: Deformable models incorporating shape priors have proved to be a successful approach in segmenting anatomical regions and specific structures in medical images. This paper introduces weighted shape priors for deformable models in the context of 3D magnetic resonance (MR) image segmentation of the bony elements of the human hip joint. The fully automated approach allows the focusing of the shape model energy to a priori selected anatomical structures or regions of clinical interest by preferentially ordering the shape representation (or eigen-modes) within this type of model to the highly weighted areas. This focused shape model improves accuracy of the shape constraints in those regions compared to standard approaches. The proposed method achieved femoral head and acetabular bone segmentation mean absolute surface distance errors of 0.55±0.18mm and 0.75±0.20mm respectively in 35 3D unilateral MR datasets from 25 subjects acquired at 3T with different limited field of views for individual bony components of the hip joint.
    Medical image analysis 02/2014; 18(3):567-578. DOI:10.1016/j.media.2014.02.002 · 3.09 Impact Factor

Publication Stats

3k Citations
558.88 Total Impact Points

Institutions

  • 1989–2015
    • University of Queensland
      • • School of Information Technology and Electrical Engineering
      • • School of Mathematics and Physics
      Brisbane, Queensland, Australia
  • 2011–2013
    • The Australian e-Health Research Centre
      Brisbane, Queensland, Australia
    • Chongqing University
      • School of Software Engineering
      Chongqing, Chongqing Shi, China
    • The Florey Institute of Neuroscience and Mental Health
      Melbourne, Victoria, Australia
  • 2012
    • Royal Children's Hospital Brisbane
      Brisbane, Queensland, Australia
    • Wuhan General Hospital of Guangzhou Military Command
      Wu-han-shih, Hubei, China
    • University of Freiburg
      • Department of Microsystems Engineering (IMTEK)
      Freiburg, Baden-Württemberg, Germany
  • 2004–2012
    • Zhejiang University
      • Department of Biomedical Engineering
      Hangzhou, Zhejiang Sheng, China
  • 2010–2011
    • Qingdao University
      Tsingtao, Shandong Sheng, China
  • 2009–2011
    • Zhejiang Sci-Tech University
      Hang-hsien, Zhejiang Sheng, China
  • 2001–2011
    • University of Tasmania
      • School of Mathematics & Physics
      Newnham, Tasmania, Australia
  • 2003–2010
    • Royal Brisbane Hospital
      • Department of Medicine
      Brisbane, Queensland, Australia
  • 2007–2009
    • The Commonwealth Scientific and Industrial Research Organisation
      Canberra, Australian Capital Territory, Australia
  • 2005
    • National High Magnetic Field Laboratory
      Tallahassee, Florida, United States
    • Harvard Medical School
      Boston, Massachusetts, United States