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  • 1. Auer, M.
    et al.
    Regitnig, P.
    Stollberger, R.
    Ebner, F.
    Holzapfel, Gerhard A.
    KTH, School of Engineering Sciences (SCI), Solid Mechanics (Dept.), Biomechanics.
    A methodology to study the morphologic changes in lesions during in vitro angioplasty using MRI and image processing2008In: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 12, no 2, p. 163-173Article in journal (Refereed)
    Abstract [en]

    The assessment of morphologic changes in atherosclerotic lesions during interventional procedures such as transluminal balloon angioplasty is an issue of highest clinical importance. We propose a methodology that allows realistic 3D morphomechanical modeling of the vessel, the plaque and the lumen at different stages of in vitro angioplasty. We elaborate on a novel device designed to guide angioplasty under controlled experimental conditions. The device allows to reproduce in vivo conditions as good as possible, i.e. axial in situ pre-stretch, 100 mmHg intraluminal pressure, 37 degrees C Tyrode solution, balloon inflation without external constraints using a high-pressure syringe and contrast medium. With a standard 1.5 T MR-system we accomplish multi-spectral images at different stages of the angioplasty experiment. After MR image acquisition the specimen is used for histopathological analysis and biomechanical tests. A segmentation process is used to generate NURBS-based 3D geometric models of the individual vessel and plaque components at different balloon pressures. Tissue components are segmented automatically using generalized gradient vector flow active contours. We investigated 10 human femoral arteries. The effects of balloon compression on the individual artery components is particularly described for two obstructed arteries with an intact collagenous cap, a pronounced lipid pool and with calcification. In both arteries we observe a significant increase in lumen area after angioplasty. Dissection between intima and media and reduction of the lipid pool are primary mechanisms of dilatation. This methodology provides a basis for studying plaque biomechanics under supra-physiological loading conditions. It has the potential to improve and validate finite element models of atherosclerotic plaques which may allow a better prediction of angioplasty procedures.

  • 2. Kiri\csli, H A
    et al.
    Schaap, Michiel
    Metz, C T
    Dharampal, A S
    Meijboom, W B
    Papadopoulou, S L
    Dedic, A
    Nieman, K
    de Graaf, Michiel A
    Meijs, M F L
    Wang, Chunliang
    Center for Medical Imaging Science and Visualization, Dept.of Medical and Health Sciences, Linköping University, Linköping.
    Walsum, Theo van
    Standardized evaluation framework for evaluating coronary artery stenosis detection, stenosis quantification and lumen segmentation algorithms in computed tomography angiography2013In: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 17, no 8, p. 859-876Article in journal (Refereed)
    Abstract [en]

    Though conventional coronary angiography (CCA) has been the standard of reference for diagnosing coronary artery disease in the past decades, computed tomography angiography (CIA) has rapidly emerged, and is nowadays widely used in clinical practice. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the performance of the algorithms devised to detect and quantify the coronary artery stenoses, and to segment the coronary artery lumen in CIA data. The objective of this evaluation framework is to demonstrate the feasibility of dedicated algorithms to: (I) (semi-)automatically detect and quantify stenosis on CIA, in comparison with quantitative coronary angiography (QCA) and CIA consensus reading, and (2) (semi-)automatically segment the coronary lumen on CIA, in comparison with expert's manual annotation. A database consisting of 48 multicenter multivendor cardiac CIA datasets with corresponding reference standards are described and made available. The algorithms from 11 research groups were quantitatively evaluated and compared. The results show that (1) some of the current stenosis detection/quantification algorithms may be used for triage or as a second-reader in clinical practice, and that (2) automatic lumen segmentation is possible with a precision similar to that obtained by experts. The framework is open for new submissions through the website, at http://coronary.bigr.nl/stenoses/. (C) 2013 Elsevier B.V. All rights reserved.

  • 3. Mazza, E.
    et al.
    Nava, A.
    Bauer, M.
    Winter, R.
    Bajka, M.
    Holzapfel, Gerhard A.
    Mechanical properties of the human uterine cervix: An in vivo study2006In: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 10, no 2, p. 125-136Article in journal (Refereed)
    Abstract [en]

    Experimental results of in vivo measurements to characterize the mechanical behaviour of human uterine cervices are documented. Aspiration experiments were performed on eight uteri in vivo, before vaginal/abdominal hysterectomy, and four uteri were also tested ex vivo, approximately 1.5 h after extraction. The reproducibility of the mechanical data from the in vivo aspiration experiments has been analysed. For an introduced stiffness parameter the organ specific SD is 22%, so that the proposed experimental procedure allows detections of 30% changes with respect to a reference value of the stiffness parameter, A comparison of in vivo and ex vivo data from the same organ has shown that: (i) the ex vivo mechanical response of the uterine cervix tissue does not differ considerably from that observed in vivo; (ii) some differences can be identified in tissue pre-conditioning with ex vivo showing a stronger history dependence with respect to in vivo; (iii) the differences in the time dependence of the mechanical response are not significant and might be masked by the variability of the measured data. This study represents a first step of a clinical application aiming at analysing the mechanical response of normal cervical tissue at different gestational ages, and identifying the mechanical properties that characterize pathologic conditions such as cervical insufficiency leading to preterm delivery.

  • 4.
    Moreno, Rodrigo
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical Image Processing and Visualization. Linköping University.
    Smedby, Örjan
    KTH, School of Technology and Health (STH), Medical Engineering, Medical Image Processing and Visualization. Linköping University.
    Gradient-Based Enhancement of Tubular Structures in Medical Images2015In: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 26, no 1, p. 19-29Article in journal (Refereed)
    Abstract [en]

    Vesselness filters aim at enhancing tubular structures in medical images. The most popular vesselness filters are based on eigenanalyses of the Hessian matrix computed at different scales. However, Hessian-based methods have well-known limitations, most of them related to the use of second order derivatives. In this paper, we propose an alternative strategy in which ring-like patterns are sought in the local orientation distribution of the gradient. The method takes advantage of symmetry properties of ring-like patterns in the spherical harmonics domain. For bright vessels, gradients not pointing towards the center are filtered out from every local neighborhood in a first step. The opposite criterion is used for dark vessels. Afterwards, structuredness, evenness and uniformness measurements are computed from the power spectrum in spherical harmonics of both the original and the half-zeroed orientation distribution of the gradient. Finally, the features are combined into a single vesselness measurement. Alternatively, a structure tensor that is suitable for vesselness can be estimated before the analysis in spherical harmonics. The two proposed methods are called Ring Pattern Detector (RPD) and Filtered Structure Tensor (FST) respectively. Experimental results with computed tomography angiography data show that the proposed filters perform better compared to the state-of-the-art.

  • 5. Rosbacke, M.
    et al.
    Lindeberg, Tony
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Björkman, E.
    Roland, P. E.
    Evaluation of using absolute versus relative base level when analyzing brain activation images using the scale-space primal sketch2001In: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 5, no 2, p. 89-110Article in journal (Refereed)
    Abstract [en]

    A dominant approach to brain mapping is to define functional regions in the brain by analyzing images of brain activation obtained from positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). This paper presents an evaluation of using one such tool, called the scale-space primal sketch, for brain activation analysis. A comparison is made concerning two possible definitions of a significance measure of blob structures in scale-space, where local contrast is measured either relative to a local or global reference level. Experiments on real brain data show that (i) the global approach with absolute base level has a higher degree of correspondence to a traditional statistical method than a local approach with relative base level, and that (ii) the global approach with absolute base level gives a higher significance to small blobs that are superimposed on larger scale structures, whereas the significance of isolated blobs largely remains unaffected. Relative to previously reported works, the following two technical improvements are also presented. (i) A post-processing tool is introduced for merging blobs that are multiple responses to image structures. This simplifies automated analysis from the scale-space primal sketch. (ii) A new approach is introduced for scale-space normalization of the significance measure, by collecting reference statistics of residual noise images obtained from the general Linear model.

  • 6. Schaap, Michiel
    et al.
    Metz, Coert T
    van Walsum, Theo
    van der Giessen, Alina G
    Weustink, Annick C
    Mollet, Nico R
    Bauer, Christian
    Bogunović, Hrvoje
    Castro, Carlos
    Deng, Xiang
    Wang, Chunliang
    Linköping Univ., Linköping, Sweden.
    Niessen, Wiro J.
    Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms2009In: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 13, no 5, p. 701-714Article in journal (Refereed)
    Abstract [en]

    Efficiently obtaining a reliable coronary artery centerline from computed tomography angiography data is relevant in clinical practice. Whereas numerous methods have been presented for this purpose, up to now no standardized evaluation methodology has been published to reliably evaluate and compare the performance of the existing or newly developed coronary artery centerline extraction algorithms. This paper describes a standardized evaluation methodology and reference database for the quantitative evaluation of coronary artery centerline extraction algorithms. The contribution of this work is fourfold: (1) a method is described to create a consensus centerline with multiple observers, (2) well-defined measures are presented for the evaluation of coronary artery centerline extraction algorithms, (3) a database containing 32 cardiac CTA datasets with corresponding reference standard is described and made available. and (4) 13 coronary artery centerline extraction algorithms, implemented by different research groups, are quantitatively evaluated and compared. The presented evaluation framework is made available to the medical imaging community for benchmarking existing or newly developed coronary centerline extraction algorithms.

  • 7. Zheng, Guoyan
    et al.
    Chu, Chengwen
    Belav‵y, Daniel L
    Ibragimov, Bulat
    Korez, Robert
    Vrtovec, Toma\vz
    Hutt, Hugo
    Everson, Richard
    Meakin, Judith
    Andrade, Isabel L\uopez
    Wang, Chunliang
    Sectra, Linköping, Sweden.
    Li, Shuo
    Evaluation and comparison of 3D intervertebral disc localization and segmentation methods for 3D T2 MR data: A grand challenge2017In: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 35, p. 327-344Article in journal (Refereed)
    Abstract [en]

    The evaluation of changes in Intervertebral Discs (IVDs) with 3D Magnetic Resonance (MR) Imaging (MRI) can be of interest for many clinical applications. This paper presents the evaluation of both IVD localization and IVD segmentation methods submitted to the Automatic 3D MRI IVD Localization and Segmentation challenge, held at the 2015 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2015) with an on-site competition. With the construction of a manually annotated reference data set composed of 25 3D T2-weighted MR images acquired from two different studies and the establishment of a standard validation framework, quantitative evaluation was performed to compare the results of methods submitted to the challenge. Experimental results show that overall the best localization method achieves a mean localization distance of 0.8 mm and the best segmentation method achieves a mean Dice of 91.8%, a mean average absolute distance of 1.1 mm and a mean Hausdorff distance of 4.3 mm, respectively. The strengths and drawbacks of each method are discussed, which provides insights into the performance of different IVD localization and segmentation methods.

  • 8. Zhuang, Xiahai
    et al.
    Li, Lei
    Payer, Christian
    Štern, Darko
    Urschler, Martin
    Heinrich, Mattias P
    Oster, Julien
    Wang, Chunliang
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Medical Imaging.
    Smedby, Örjan
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Medical Imaging.
    Bian, Cheng
    Yang, Xin
    Heng, Pheng-Ann
    Mortazi, Aliasghar
    Bagci, Ulas
    Yang, Guanyu
    Sun, Chenchen
    Galisot, Gaetan
    Ramel, Jean-Yves
    Brouard, Thierry
    Tong, Qianqian
    Si, Weixin
    Liao, Xiangyun
    Zeng, Guodong
    Shi, Zenglin
    Zheng, Guoyan
    Wang, Chengjia
    MacGillivray, Tom
    Newby, David
    Rhode, Kawal
    Ourselin, Sebastien
    Mohiaddin, Raad
    Keegan, Jennifer
    Firmin, David
    Yang, Guang
    Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge.2019In: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 58, article id 101537Article in journal (Refereed)
    Abstract [en]

    Knowledge of whole heart anatomy is a prerequisite for many clinical applications. Whole heart segmentation (WHS), which delineates substructures of the heart, can be very valuable for modeling and analysis of the anatomy and functions of the heart. However, automating this segmentation can be challenging due to the large variation of the heart shape, and different image qualities of the clinical data. To achieve this goal, an initial set of training data is generally needed for constructing priors or for training. Furthermore, it is difficult to perform comparisons between different methods, largely due to differences in the datasets and evaluation metrics used. This manuscript presents the methodologies and evaluation results for the WHS algorithms selected from the submissions to the Multi-Modality Whole Heart Segmentation (MM-WHS) challenge, in conjunction with MICCAI 2017. The challenge provided 120 three-dimensional cardiac images covering the whole heart, including 60 CT and 60 MRI volumes, all acquired in clinical environments with manual delineation. Ten algorithms for CT data and eleven algorithms for MRI data, submitted from twelve groups, have been evaluated. The results showed that the performance of CT WHS was generally better than that of MRI WHS. The segmentation of the substructures for different categories of patients could present different levels of challenge due to the difference in imaging and variations of heart shapes. The deep learning (DL)-based methods demonstrated great potential, though several of them reported poor results in the blinded evaluation. Their performance could vary greatly across different network structures and training strategies. The conventional algorithms, mainly based on multi-atlas segmentation, demonstrated good performance, though the accuracy and computational efficiency could be limited. The challenge, including provision of the annotated training data and the blinded evaluation for submitted algorithms on the test data, continues as an ongoing benchmarking resource via its homepage (www.sdspeople.fudan.edu.cn/zhuangxiahai/0/mmwhs/).

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