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ABSTRACT: Continuous magnetic resonance (MR) imaging is a promising tool for image-guided cardiac interventions. However, cardiac imaging is complicated by both, cardiac and respiratory motion. While the former is commonly addressed by cardiac gating, the latter requires a real time motion compensation. Here, a new image based motion estimation is proposed, extending the initial Horn & Schunck optical flow approach by an additional regularization term. This term allows to integrate displacement of physiological landmarks, which are obtained in a preparation step using pattern matching. The proposed method was evaluated on the left ventricle (LV) of cardiac MR-images and showed a better estimation accuracy compared to the original Horn & Schunck approach.
Image Processing (ICIP), 2010 17th IEEE International Conference on; 10/2010
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ABSTRACT: MR‐guided high intensity focused ultrasound (HIFU) has evolved into a promising non‐invasive technique for the ablation of pathological tissue in abdominal organs. However, since the high perfusion rates of these organs lead to effective cooling, sustained sonications of 30–90 s are required to achieve a sufficiently high temperature elevation to induce necrosis. This is complicated by the constant displacement of the target due to the respiratory cycle. This study proposes sub‐second 3D HIFU‐beam steering under MR‐guidance for the near real‐time compensation of respiratory motion as a possible solution. The target position is observed in 3D space by coupling rapid 2D MR‐imaging with prospective slice tracking (PST) based on pencil‐beam navigator echoes. Continuous real‐time image processing provides temperature maps, thermal dose estimates and the target position at a frequency of 10 Hz and an update latency of less than 120 ms. The suggested method is evaluated with phantom experiments and its feasibility is verified in‐vivo with an ablation experiment on a porcine kidney where it allows to achieve a thermal energy deposition which is comparable to static control experiments.
AIP Conference Proceedings. 03/2010; 1215(1):239-242.
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ABSTRACT: MR-thermometry allows monitoring of the local temperature evolution during minimally invasive interventional therapies. However, for the particular case of MR-thermometry in the human breast, magnetic field variations induced by the respiratory cycle lead to phase fluctuations requiring a suitable correction strategy to prevent thermometry errors. For this purpose a look-up-table-based multibaseline approach as well as a model-based correction algorithm were applied to MR-thermometry to correct for the periodic magnetic field changes. The proposed correction method is compatible with a variety of sensors monitoring the current respiratory state. The ability to remove phase artefacts during MR-thermometry of the human breast was demonstrated experimentally in five healthy volunteers during 3 min of free-breathing using pencil-beam navigators for respiratory control. An increase of 170-530% in temperature precision was observed for the look-up-table-based approach, whereas a further improvement by 16-36% could be achieved by applying the extended model-based correction.
Magnetic Resonance in Medicine 05/2009; 61(6):1494-9. · 2.96 Impact Factor
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ABSTRACT: Contrast-enhanced dynamic magnetic resonance imaging (MRI) acquisition is a common method to retrieve functional information from organs in the human body. Applied to the kidney, the observation of the signal evolution in the cortex of a MR-series gives access to the renal perfusion and filtration. The glomerular filtration rate (GFR) is in particular the most useful quantitative index of renal function. Since the rapid bolus passage hampers the use of gated sequences, fast sequences have to be employed to enable a data acquisition while free-breathing. As a result, the acquired data contains motion artifacts caused by the respiratory cycle, spontaneous movements and drifts which limit quantitative analysis of the data. Although these problems can in principle be addressed with motion correction algorithms applied in a post processing step, additional challenges arise from the fact that image amplitude changes not only due to motion but also due to the contrast change during bolus passage. This study proposes a 2D region tracking method for retrospective motion correction without sacrificing temporal resolution which addresses the latter point by a preparative learning phase
Image Processing, 2006 IEEE International Conference on; 11/2006
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ABSTRACT: Magnetic resonance (MR) systems can be used to monitor temperature changes in and around a treated region during an hyperthermic ablation procedure. Dynamic temperature monitoring allows on-line prediction of cellular destruction during the intervention. However, organ displacements due to physiological activity (respiratory cycle) may induce important artifacts in computed temperature maps. In addition, focused ultrasound (FUS) is an extra-corporal heating device which makes possible to perform local hyperthermia non-invasively. For intervention on mobile organs, the position of the focal point must be adjusted dynamically to track the targeted pathologic tissue. Without such corrections, treatment is inefficient or may induce unwanted destruction of healthy tissue. In this paper, image processing methods are developed to propose an efficient solution to correct on-line motion artifacts on temperature maps, and to adjust the focal point position of the FUS device in order to track the targeted organ moving
Image Processing, 2006 IEEE International Conference on; 11/2006
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ABSTRACT: FMRI is a technique using BOLD contrast to identify areas of cerebral activity. Large vessels contribution to this signal induces a delay in the measured response. It is therefore imperative to precisely colocalize brain activity and large veins. MR venography is an acquisition procedure using phase variations to reinforce cerebral vasculature on anatomical data. In this article, we present a method to register brain large veins and activation map in order to achieve an accurate interpretation of measured activity
Image Processing, 2006 IEEE International Conference on; 11/2006
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ABSTRACT: Magnetic resonance (MR) temperature mapping can be used to monitor temperature changes during minimally invasive thermal therapies during the procedure. Robust 3D estimation of organ displacement during the intervention is hardly feasible due to technical limitations (spatial and temporal resolution are not sufficient to perform classic 3D registration methods on anatomical images). However, organ displacements due to physiological activity (heart and respiration) may induce important artifacts on apparent temperature maps and prevent the treatment of a tumor with an external heating device. Recent development has allowed increasing external information for 3D motion estimation. This paper presents a new method that exploits image information for robust 3D motion estimation from MR images, in order to make possible the treatment of organs such as the kidney, and to improve the precision of temperature estimation using the proton resonance frequency (PRF) shift. The motion estimation described in this paper consists of two steps: a reference volume is initially computed in a preparation phase; during the intervention a 3D displacement vector is estimated on-line for each pixel of the acquired images by using this reference volume. This method can be applied to any type of image sequences and thus is not restricted to MR images.
Image Processing, 2005. ICIP 2005. IEEE International Conference on; 10/2005
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ABSTRACT: Magnetic resonance (MR) temperature mapping can be used to monitor temperature changes in minimally invasive thermal therapies during the procedure. However, organs displacements due to physiological activity (heart and respiration) may induce important artifacts on apparent temperature maps. This paper presents a new method for motion quantification and correction in such MR images, in order to improve the precision of temperature estimation using the proton resonance frequency (PRF) shift. The PRF shift technique gives an estimate of the relative temperature variation, comparing contrast between dynamically acquired images and a reference data sets. The correction method described in this paper consists of two steps: a motion atlas is initially computed in a preparation phase; during the intervention, the appropriate reference image is chosen from the atlas, allowing correct computation of the temperature map despite tissue motion. This method can be applied to any type of image sequences and is not restricted to MR images.
Image Processing, 2004. ICIP '04. 2004 International Conference on; 11/2004
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ABSTRACT: Magnetic resonance (MR) systems can be used to monitor temperature changes in and around a treated region during an hyperthermic ablation procedure. Dynamic temperature monitoring allows on-line prediction of cellular destruction during the intervention. MRI systems associate each volume unit with a complex number. Phase component is 2pi periodic (it is a function of the wrapped phase) and accounts for noise sources present in MR imaging. Robust spatial phase unwrapping is a necessary prerequisite for several applications. This study proposes a spatial phase unwrapping algorithm for MR images, allowing a real time implementation for on-line temperature monitoring.
Image Processing, 2007. ICIP 2007. IEEE International Conference on;
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ABSTRACT: Real-time magnetic resonance (MR) thermometry provides continuous temperature mapping inside the human body and is therefore a promising tool to monitor and control interventional therapies based on thermal ablation. Temperature information must be mapped to a reference position of observed organs in order to allow thermal dose computation, as the history of temperature is required for each pixel. Motion compensated MR-thermometry for thermotherapy has to cope with radio-frequency (RF) artifacts and relaxation-time changes of the monitored tissue. While purely optical-flow-based realignment may lead to temperature map computation errors for the case of local or global intensity changes, principal component analysis based realignment results in accurately registered temperature maps. The motion estimation process described in this paper consists of two steps : a parameterized flow models is initially computed using a principal component analysis during a preparative learning step; during the intervention, motion is characterized with a small set of parameters using a least square solver.
Image Processing, 2007. ICIP 2007. IEEE International Conference on;
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