MRI-based attenuation correction of PET images in clinical PET/MR
Based on our previous approach we seek to develop a robust algorithm for AC in PET/MR brain images and extend this atlas-based approach to whole body.
Given the access to a prototype PET/MR system at the University Hospital Tübingen we intend to validate and fine-tune our MR-based attenuation correction with patient data.
Attenuation correction (AC) is mandatory for quantitative Positron Emission Tomography (PET) imaging. Without attenuation correction activity concentrations on PET images are biased depending on the tissue density.
The lack of conventional X-ray transmission sources in PET/MR systems requires alternative approaches for attenuation correction as a pre-requisite for quantitative PET in combined PET/MR. MR image values do not correlate with attenuation coefficients of the tissue, and therefore can not be directly used for PET-AC.
We apply an approach based on a database of coregistered PET/CT and MRI datasets with pattern recognition methods to generate attenuation maps from MR data.
For a patient subject to MR-AC, atlas MR datasets are co-registered to the MR image volume of the PET/MR patient. The resulting transformations are applied to the corresponding CT datasets from the database. Subsequently, a pattern recognition approach is used to match the MR image of the patient with the appropriate CT information from that MR-CT datasets that best match the patient information. This voxel-based approach can merge partial sub-volumes from independent data sets into a single CT-volume that is used for MR-AC of the patients. The generated "Pseudo CT" is then converted to an attenuation map using a piecewise linear transformation.
Journal of Nuclear Medicine, 54(10):1768-1774, 2013 (article)
Hybrid PET/MR systems have recently entered clinical practice. Thus, the accuracy of MR-based attenuation correction in simultaneously acquired data can now be investigated. We assessed the accuracy of 4 methods of MR-based attenuation correction in lesions within soft tissue, bone, and MR susceptibility artifacts: 2 segmentation-based methods (SEG1, provided by the manufacturer, and SEG2, a method with atlas-based susceptibility artifact correction); an atlas- and pattern recognition–based method (AT&PR), which also used artifact correction; and a new method combining AT&PR and SEG2 (SEG2wBONE). Methods: Attenuation maps were calculated for the PET/MR datasets of 10 patients acquired on a whole-body PET/MR system, allowing for simultaneous acquisition of PET and MR data. Eighty percent iso-contour volumes of interest were placed on lesions in soft tissue (n = 21), in bone (n = 20), near bone (n = 19), and within or near MR susceptibility artifacts (n = 9). Relative mean volume-of-interest differences were calculated with CT-based attenuation correction as a reference. Results: For soft-tissue lesions, none of the methods revealed a significant difference in PET standardized uptake value relative to CT-based attenuation correction (SEG1, −2.6% ± 5.8%; SEG2, −1.6% ± 4.9%; AT&PR, −4.7% ± 6.5%; SEG2wBONE, 0.2% ± 5.3%). For bone lesions, underestimation of PET standardized uptake values was found for all methods, with minimized error for the atlas-based approaches (SEG1, −16.1% ± 9.7%; SEG2, −11.0% ± 6.7%; AT&PR, −6.6% ± 5.0%; SEG2wBONE, −4.7% ± 4.4%). For lesions near bone, underestimations of lower magnitude were observed (SEG1, −12.0% ± 7.4%; SEG2, −9.2% ± 6.5%; AT&PR, −4.6% ± 7.8%; SEG2wBONE, −4.2% ± 6.2%). For lesions affected by MR susceptibility artifacts, quantification errors could be reduced using the atlas-based artifact correction (SEG1, −54.0% ± 38.4%; SEG2, −15.0% ± 12.2%; AT&PR, −4.1% ± 11.2%; SEG2wBONE, 0.6% ± 11.1%). Conclusion: For soft-tissue lesions, none of the evaluated methods showed statistically significant errors. For bone lesions, significant underestimations of −16% and −11% occurred for methods in which bone tissue was ignored (SEG1 and SEG2). In the present attenuation correction schemes, uncorrected MR susceptibility artifacts typically result in reduced attenuation values, potentially leading to highly reduced PET standardized uptake values, rendering lesions indistinguishable from background. While AT&PR and SEG2wBONE show accurate results in both soft tissue and bone, SEG2wBONE uses a two-step approach for tissue classification, which increases the robustness of prediction and can be applied retrospectively if more precision in bone areas is needed.
Combined positron emission tomography (PET) and magnetic resonance imaging (MRI) is a new tool to study functional processes in the brain. Here we study brain function in response to a barrel-field stimulus simultaneously using PET, which traces changes in glucose metabolism on a slow time scale, and functional MRI (fMRI), which assesses fast vascular and oxygenation changes during activation. We found spatial and quantitative discrepancies between the PET and the fMRI activation data. The functional connectivity of the rat brain was assessed by both modalities: the fMRI approach determined a total of nine known neural networks, whereas the PET method identified seven glucose metabolism–related networks. These results demonstrate the feasibility of combined PET-MRI for the simultaneous study of the brain at activation and rest, revealing comprehensive and complementary information to further decode brain function and brain networks.
2011(MIC18.M-96), 2011 IEEE Nuclear Science Symposium, Medical Imaging Conference (NSS-MIC), October 2011 (poster)
Combined PET/MR provides simultaneous molecular and functional information in an anatomical context with unique soft tissue contrast. However, PET/MR does not support direct derivation of attenuation maps of objects and tissues within the measured PET field-of-view. Valid attenuation maps are required for quantitative PET imaging, specifically for scientific brain studies. Therefore, several methods have been proposed for MR-based attenuation correction (MR-AC). Last year, we performed an evaluation of different MR-AC methods, including simple MR thresholding, atlas- and machine learning-based MR-AC. CT-based AC served as gold standard reference. RoIs from 2 anatomic brain atlases with different levels of detail were used for evaluation of correction accuracy. We now extend our evaluation of different MR-AC methods by using an enlarged dataset of 23 patients from the integrated BrainPET/MR (Siemens Healthcare). Further, we analyze options for improving the MR-AC performance in terms of speed and accuracy. Finally, we assess the impact of ignoring BrainPET positioning aids during the course of MR-AC. This extended study confirms the overall prediction accuracy evaluation results of the first evaluation in a larger patient population. Removing datasets affected by metal artifacts from the Atlas-Patch database helped to improve prediction accuracy, although the size of the database was reduced by one half. Significant improvement in prediction speed can be gained at a cost of only slightly reduced accuracy, while further optimizations are still possible.
Lois, C., Bezrukov, I., Schmidt, H., Schwenzer, N., Werner, M., Pichler, B., Kupferschläger, J., Beyer, T.
2011(MIC3-3), 2011 IEEE Nuclear Science Symposium, Medical Imaging Conference (NSS-MIC), October 2011 (talk)
Combined whole-body PET/MR systems are being tested in clinical practice today. Integrated imaging protocols entail the use of MR contrast agents (MRCA) that could bias PET attenuation correction. In this work, we assess the effect of MRCA in PET/MR imaging. We analyze the effect of oral and intravenous MRCA on PET activity after attenuation correction. We conclude that in clinical scenarios, MRCA are not expected to lead to significant attenuation of PET signals, and that attenuation maps are not biased after the ingestion of adequate oral contrasts.
2011(MIC18.M-116), 2011 IEEE Nuclear Science Symposium, Medical Imaging Conference (NSS-MIC), October 2011 (poster)
With the recent availability of clinical whole-body PET/MRI it is possible to evaluate and further develop MR-based attenuation correction methods using simultaneously acquired PET/MR data. We present first results for MRAC on patient data acquired on a fully integrated whole-body PET/MRI (Biograph mMR, Siemens) using our method that applies atlas registration and pattern recognition (ATPR) and compare them to the segmentation-based (SEG) method provided by the manufacturer.
The ATPR method makes use of a database of previously aligned pairs of MR-CT volumes to predict attenuation values on a continuous scale. The robustness of the method in presence of MR artifacts was improved by location and size based detection. Lesion to liver and lesion to blood ratios (LLR and LBR) were compared for both methods on 29 iso-contour ROIs in 4 patients.
ATPR showed >20% higher LBR and LLR for ROIs in and >7% near osseous tissue. For ROIs in soft tissue, both methods yielded similar ratios with max. differences <6% . For ROIs located within metal artifacts in the MR image, ATPR showed >190% higher LLR and LBR than SEG, where ratios <0.1 occured. For lesions in the neighborhood of artifacts, both ratios were >15% higher for ATPR.
If artifacts in MR volumes caused by metal implants are not accounted for in the computation of attenuation maps, they can lead to a strong decrease of lesion to background ratios, even to disappearance of hot spots. Metal implants are likely to occur in the patient collective receiving combined PET/MR scans, of our first 10 patients, 3 had metal implants. Our method is currently able to account for artifacts in the pelvis caused by prostheses. The ability of the ATPR method to account for bone leads to a significant increase of LLR and LBR in osseous tissue, which supports our previous evaluations with combined PET/CT and PET/MR data. For lesions within soft tissue, lesion to background ratios of ATPR and SEG were comparable.
Lois, C., Kupferschläger, J., Bezrukov, I., Schmidt, H., Werner, M., Mannheim, J., Pichler, B., Schwenzer, N., Beyer, T.
(SST15-05 ), 97th Scientific Assemble and Annual Meeting of the Radiological Society of North America (RSNA), December 2011 (talk)
Combined PET/MR imaging entails the use of MR contrast agents (MRCA) as part of integrated protocols. We assess additional attenuation of the PET emission signals in the presence of oral and intraveneous (iv) MRCA made up of iron oxide and Gd-chelates, respectively.
METHOD AND MATERIALS
Phantom scans were performed on a clinical PET/CT (Biograph HiRez16, Siemens) and integrated whole-body PET/MR (Biograph mMR, Siemens) using oral (Lumirem) and intraveneous (Gadovist) MRCA.
Reference PET attenuation values were determined on a small-animal PET (Inveon, Siemens) using standard PET transmission imaging (TX). Seven syringes of 5mL were filled with (a) Water, (b) Lumirem_100 (100% conc.), (c) Gadovist_100 (100%), (d) Gadovist_18 (18%), (e) Gadovist_02 (0.2%), (f) Imeron-400 CT iv-contrast (100%) and (g) Imeron-400 (2.4%). The same set of syringes was scanned on CT (Sensation16, Siemens) at 120kVp and 160mAs.
The effect of MRCA on the attenuation of PET emission data was evaluated using a 20cm cylinder filled uniformly with [18F]-FDG (FDG) in water (BGD). Three 4.5cm diameter cylinders were inserted into the phantom: (C1) Teflon, (C2) Water+FDG (2:1) and (C3) Lumirem_100+FDG (2:1). Two 50mL syringes filled with Gadovist_02+FDG (Sy1) and water+FDG (Sy2) were attached to the sides of (C1) to mimick the effects of iv-contrast in vessels near bone. Syringe-to-background activity ratio was 4-to-1. PET emission data were acquired for 10min each using the PET/CT and the PET/MR. Images were reconstructed using CT- and MR-based attenuation correction.
Mean linear PET attenuation (cm-1) on TX was (a) 0.098, (b) 0.098, (c) 0.300, (d) 0.134, (e) 0.095, (f) 0.397 and (g) 0.105. Corresponding CT attenuation (HU) was: (a) 5, (b) 14, (c) 3070, (d) 1040, (e) 13, (f) 3070 and (g) 347.
Lumirem had little effect on PET attenuation with (C3) being 13% and 10% higher than (C2) on PET/CT and PET/MR, respectively. Gadovist_02 had even smaller effects with (Sy1) being 2.5% lower than (Sy2) on PET/CT and 1.2% higher than (Sy2) on PET/MR.
MRCA in high and clinically relevant concentrations have attenuation values similar to that of CT contrast and water, respectively. In clinical PET/MR scenarios MRCA are not expected to lead to significant attenuation of the PET emission signals.
Lois, C., Kupferschläger, J., Bezrukov, I., Schmidt, H., Werner, M., Mannheim, J., Pichler, B., Schwenzer, N., Beyer, T.
(OP314), Annual Congress of the European Association of Nuclear Medicine (EANM), October 2011 (talk)
PURPOSE:Combined PET/MR imaging entails the use of MR contrast agents (MRCA) as part of integrated protocols. MRCA are made up of iron oxide and Gd-chelates for oral and intravenous (iv) application, respectively. We assess additional attenuation of the PET emission signals in the presence of oral and iv MRCA.MATERIALS AND METHODS:Phantom scans were performed on a clinical PET/CT (Biograph HiRez16, Siemens) and an integrated whole-body PET/MR (Biograph mMR, Siemens). Two common MRCA were evaluated: Lumirem (oral) and Gadovist (iv).Reference PET attenuation values were determined on a dedicated small-animal PET (Inveon, Siemens) using equivalent standard PET transmission source imaging (TX). Seven syringes of 5mL were filled with (a) Water, (b) Lumirem_100 (100% concentration), (c) Gadovist_100 (100%), (d) Gadovist_18 (18%), (e) Gadovist_02 (0.2%), (f) Imeron-400 CT iv-contrast (100%) and (g) Imeron-400 (2.4%). The same set of syringes was scanned on CT (Sensation16, Siemens) at 120kVp and 160mAs.The effect of MRCA on the attenuation of PET emission data was evaluated using a 20cm cylinder filled uniformly with [18F]-FDG (FDG) in water (BGD). Three 4.5cm diameter cylinders were inserted into the phantom: (C1) Teflon, (C2) Water+FDG (2:1) and (C3) Lumirem_100+FDG (2:1). Two 50mL syringes filled with Gadovist_02+FDG (Sy1) and water+FDG (Sy2) were attached to the sides of (C1) to mimick the effects of iv-contrast in vessels near bone. Syringe-to-background activity ratio was 4-to-1.PET emission data were acquired for 10min each using the PET/CT and the PET/MR. Images were reconstructed using CT- and MR-based attenuation correction (AC). Since Teflon is not correctly identified on MR, PET(/MR) data were reconstructed using MR-AC and CT-AC.RESULTS:Mean linear PET attenuation (cm-1) on TX was (a) 0.098, (b) 0.098, (c) 0.300, (d) 0.134, (e) 0.095, (f) 0.397 and (g) 0.105. Corresponding CT attenuation (HU) was: (a) 5, (b) 14, (c) 3070, (d) 1040, (e) 13, (f) 3070 and (g) 347.Lumirem had little effect on PET attenuation with (C3) being 13%, 10% and 11% higher than (C2) on PET/CT, PET/MR with MR-AC, and PET/MR with CT-AC, respectively. Gadovist_02 had even smaller effects with (Sy1) being 2.5% lower, 1.2% higher, and 3.5% lower than (Sy2) on PET/CT, PET/MR with MR-AC and PET/MR with CT-AC, respectively.CONCLUSION:MRCA in high and clinically relevant concentrations have attenuation values similar to that of CT contrast and water, respectively. In clinical PET/MR scenarios MRCA are not expected to lead to significant attenuation of the PET emission signals.
Brendle, C., Sauter, A., Schmidt, H., Schraml, C., Bezrukov, I., Martirosian, P., Hetzel, J., Müller, M., Claussen, C., Schwenzer, N., Pfannenberg, C.
Magnetic Resonance Materials in Physics, Biology and Medicine, 24(Supplement 1):141, 28th annual scientific meeting of the European Society for Magnetic Resonance in Medicine and Biology (ESMRB), October 2011 (poster)
Purpose/Introduction: Lung cancer is among the most frequent cancers (1). Exact determination of tumour extent and viability is crucial for adequate therapy guidance. [18F]-FDG-PET allows accurate staging and the evaluation
of therapy response based on glucose metabolism. Diffusion weighted MRI (DWI) is another promising tool for the evaluation of tumour viability (2,3). The aim of the study was the simultaneous PET-MR acquisition in lung cancer patients and correlation of PET and MR data.
Subjects and Methods: Seven patients (age 38-73 years, mean 61 years) with highly suspected or known bronchial carcinoma were examined. First, a [18F]-FDG-PET/CT was performed (injected dose: 332-380 MBq). Subsequently, patients were examined at the whole-body MR/PET (Siemens Biograph mMR). The MRI is a modified 3T Verio whole body system with a magnet bore of 60 cm (max. amplitude gradients 45 mT/m, max. slew rate 200 T/m/s). Concerning the PET, the whole-body MR/PET system comprises
56 detector cassettes with a 59.4 cm transaxial and 25.8 cm axial FoV. The following parameters for PET acquisition were applied: 2 bed positions, 6 min/bed with an average uptake time of 124 min after injection (range: 110-143 min). The attenuation correction of PET data was conducted with a segmentation-based method provided by the manufacturer. Acquired PET data were reconstructed with an iterative 3D OSEM algorithm using 3 iterations and 21 subsets, Gaussian filter of 3 mm. DWI MR images were recorded simultaneously for each bed using two b-values (0/800 s/mm2). SUVmax and ADCmin were assessed in a ROI analysis. The following ratios were calculated: SUVmax(tumor)/SUVmean(liver) and ADCmin(tumor)/ADCmean(muscle). Correlation between SUV and ADC was analyzed (Pearson’s correlation).
Results: Diagnostic scans could be obtained in all patients with good tumour delineation. The spatial matching of PET and DWI data was very exact. Most tumours showed a pronounced FDG-uptake in combination with decreased ADC values. Significant correlation was found between SUV and ADC ratios (r = -0.87, p = 0.0118).
Discussion/Conclusion: Simultaneous MR/PET imaging of lung cancer is feasible. The whole-body MR/PET system can provide complementary information regarding tumour viability and cellularity which could facilitate a more profound tumour characterization. Further studies have to be done to evaluate the importance of these parameters for therapy decisions and monitoring
Journal of Nuclear Medicine, 52(9):1392-1399, September 2011 (article)
PET/MRI is an emerging dual-modality imaging technology that requires new approaches to PET attenuation correction (AC). We assessed 2 algorithms for whole-body MRI-based AC (MRAC): a basic MR image segmentation algorithm and a method based on atlas registration and pattern recognition (AT&PR).
Eleven patients each underwent a whole-body PET/CT study and a separate multibed whole-body MRI study. The MR image segmentation algorithm uses a combination of image thresholds, Dixon fat-water segmentation, and component analysis to detect the lungs. MR images are segmented into 5 tissue classes (not including bone), and each class is assigned a default linear attenuation value. The AT&PR algorithm uses a database of previously aligned pairs of MRI/CT image volumes. For each patient, these pairs are registered to the patient MRI volume, and machine-learning techniques are used to predict attenuation values on a continuous scale. MRAC methods are compared via the quantitative analysis of AC PET images using volumes of interest in normal organs and on lesions. We assume the PET/CT values after CT-based AC to be the reference standard.
In regions of normal physiologic uptake, the average error of the mean standardized uptake value was 14.1% ± 10.2% and 7.7% ± 8.4% for the segmentation and the AT&PR methods, respectively. Lesion-based errors were 7.5% ± 7.9% for the segmentation method and 5.7% ± 4.7% for the AT&PR method.
The MRAC method using AT&PR provided better overall PET quantification accuracy than the basic MR image segmentation approach. This better quantification was due to the significantly reduced volume of errors made regarding volumes of interest within or near bones and the slightly reduced volume of errors made regarding areas outside the lungs.
Schmidt, H., Schwenzer, N., Bezrukov, I., Kolb, A., Mantlik, F., Kupferschläger, J., Lois, C., Sauter, A., Brendle, C., Pfannenberg, C., Pichler, B.
2011(J2-8), 2011 IEEE Nuclear Science Symposium, Medical Imaging Conference (NSS-MIC), October 2011 (talk)
First clinical fully integrated whole-body PET/MR scanners are just entering the field. Here, we present studies toward quantification accuracy and variation within the PET field of view of small lesions from our BrainPET/MRI, a dedicated clinical brain scanner which was installed three years ago in Tbingen. Also, we present first results for patient and phantom scans of a fully integral whole-body PET/MRI, which was installed two months ago at our department. The quantification accuracy and homogeneity of the BrainPET-Insert (Siemens Medical Solutions, Germany) installed inside the magnet bore of a clinical 3T MRI scanner (Magnetom TIM Trio, Siemens Medical Solutions, Germany) was evaluated by using eight hollow spheres with inner diameters from 3.95 to 7.86 mm placed at different positions inside a homogeneous cylinder phantom with an 9:1 and 6:1 sphere to background ratio. The quantification accuracy for small lesions at different positions in the PET FoV shows a standard deviation of up to 11% and is acceptable for quantitative brain studies where the homogeneity of quantification on the entire FoV is essental. Image quality and resolution of the new Siemens whole-body PET/MR system (Biograph mMR, Siemens Medical Solutions, Germany) was evaluated according to the NEMA NU2 2007 protocol using a body phantom containing six spheres with inner diameter from 10 to 37 mm at sphere to background ratios of 8:1 and 4:1 and the F-18 point sources located at different positions inside the PET FoV, respectively. The evaluation of the whole-body PET/MR system reveals a good PET image quality and resolution comparable to state-of-the-art clinical PET/CT scanners. First images of patient studies carried out at the whole-body PET/MR are presented highlighting the potency of combined PET/MR imaging.
Sauter, A., Schmidt, H., Gueckel, B., Brendle, C., Bezrukov, I., Mantlik, F., Kolb, A., Mueller, M., Reimold, M., Federmann, B., Hetzel, J., Claussen, C., Pfannenberg, C., Horger, M., Pichler, B., Schwenzer, N.
(T110), 2011 World Molecular Imaging Congress (WMIC), September 2011 (talk)
Hybrid imaging modalities such as [18F]FDG-PET/CT are superior in staging of e.g. lung cancer disease compared with stand-alone modalities. Clinical PET/MRI systems are about to enter the field of hybrid imaging and offer potential advantages. One added value could be a deeper insight into the tumor metabolism and tumorigenesis due to the combination of PET and dedicated MR methods such as MRS and DWI. Additionally, therapy monitoring of diffucult to diagnose disease such as chronic sclerodermic GvHD (csGvHD) can potentially be improved by this combination. We have applied PET/MRI in 3 patients with lung cancer and 4 patients with csGvHD before and during therapy. All 3 patients had lung cancer confirmed by histology (2 adenocarcinoma, 1 carcinoid). First, a [18F]FDG-PET/CT was performed with the following parameters: injected dose 351.7±25.1 MBq, uptake time 59.0±2.6 min, 3 min/bed. Subsequently, patients were brought to the PET/MRI imaging facility. The whole-body PET/MRI Biograph mMR system comprises 56 detector cassettes with a 59.4 cm transaxial and 25.8 cm axial FoV. The MRI is a modified Verio system with a magnet bore of 60 cm. The following parameters for PET acquisition were applied: uptake time 121.3±2.3 min, 3 bed positions, 6 min/bed. T1w, T2w, and DWI MR images were recorded simultaneously for each bed. Acquired PET data were reconstructed with an iterative 3D OSEM algorithm using 3 iterations and 21 subsets, Gaussian filter of 3 mm. The 4 patients with GvHD were brought to the brainPET/MRI imaging facility 2:10h-2:28h after tracer injection. A 9 min brainPET-acquisition with simultaneous MRI of the lower extremities was accomplished. MRI examination included T1-weighted (pre and post gadolinium) and T2-weighted sequences. Attenuation correction was calculated based on manual bone segmentation and thresholds for soft tissue, fat and air. Soleus muscle (m), crural fascia (f1) and posterior crural intermuscular septum fascia (f2) were surrounded with ROIs based on the pre-treatment T1-weighted images and coregistered using IRW (Siemens). Fascia-to-muscle ratios for PET (f/m), T1 contrast uptake (T1_post-contrast_f-pre-contrast_f/post-contrast_m-pre-contrast_m) and T2 (T2_f/m) were calculated. Both patients with adenocarcinoma show a lower ADC value compared with the carcinoid patient suggesting a higher cellularity. This is also reflected in FDG-PET with higher SUV values. Our initial results reveal that PET/MRI can provide complementary information for a profound tumor characterization and therapy monitoring. The high soft tissue contrast provided by MRI is valuable for the assessment of the fascial inflammation. While in the first patient FDG and contrast uptake as well as edema, represented by T2 signals, decreased with ongoing therapy, all parameters remained comparatively stable in the second patient. Contrary to expectations, an increase in FDG uptake of patient 3 and 4 was accompanied by an increase of the T2 signals, but a decrease in contrast uptake. These initial results suggest that PET/MRI provides complementary information of the complex disease mechanisms in fibrosing disorders.
In Computational Photography: Methods and Applications, pages: 395-418, Digital Imaging and Computer Vision, (Editors: Lukac, R.), CRC Press, Boca Raton, FL, USA, 2010 (inbook)
We aim to color greyscale images automatically, without any manual intervention. The color proposition could then be interactively corrected by user-provided color landmarks if necessary. Automatic colorization is nontrivial since there is usually no one-to-one correspondence between color and local texture. The contribution of our framework is that we deal directly with multimodality and estimate, for each pixel of the image to be colored, the probability distribution of all possible colors, instead of choosing the most probable color at the local level. We also predict the expected variation of color at each pixel, thus defining a non-uniform spatial coherency criterion. We then use graph cuts to maximize the probability of the whole colored image at the global level. We work in the L-a-b color space in order to approximate the human perception of distances between colors, and we use machine learning tools to extract as much information as possible from a dataset of colored examples. The resulting algorithm is fast, designed to be more robust to texture noise, and is above all able to deal with ambiguity, in contrary to previous approaches.
2010(M08-4), 2010 Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC), November 2010 (talk)
Combined PET/MR provides at the same time molecular and functional imaging as well as excellent soft tissue contrast. It does not allow one to directly measure the attenuation properties of scanned tissues, despite the fact that accurate attenuation maps are necessary for quantitative PET imaging. Several methods have therefore been proposed for MR-based attenuation correction (MR-AC). So far, they have only been evaluated on data acquired from separate MR and PET scanners. We evaluated several MR-AC methods on data from 10 patients acquired on a combined BrainPET/MR scanner. This allowed the consideration of specific PET/MR issues, such as the RF coil that attenuates and scatters 511 keV gammas. We evaluated simple MR thresholding methods as well as atlas and machine learning-based MR-AC. CT-based AC served as gold standard reference. To comprehensively evaluate the MR-AC accuracy, we used RoIs from 2 anatomic brain atlases with different levels of detail.
Visual inspection of the PET images indicated that even the basic FLASH threshold MR-AC may be sufficient for several applications. Using a UTE sequence for bone prediction in MR-based thresholding occasionally led to false prediction of bone tissue inside the brain, causing a significant overestimation of PET activity. Although it yielded a lower mean underestimation of activity, it exhibited the highest variance of all methods. The atlas averaging approach had a smaller mean error, but showed high maximum overestimation on the RoIs of the more detailed atlas. The Nave Bayes and Atlas-Patch MR-AC yielded the smallest variance, and the Atlas-Patch also showed the smallest mean error.
In conclusion, Atlas-based AC using only MR information on the BrainPET/MR yields a high level of accuracy that is sufficient for clinical quantitative imaging requirements. The Atlas-Patch approach was superior to alternative atlas-based methods, yielding a quantification error below 10% for all RoIs except very small ones.
In Proceedings of the MICCAI 2009 Workshop on Probabilistic Models for Medical Image Analysis , pages: 220-231, (Editors: W Wells and S Joshi and K Pohl), PMMIA, September 2009 (inproceedings)
We present a methodology for incorporating prior knowledge
on class probabilities into the registration process. By using knowledge
from the imaging modality, pre-segmentations, and/or probabilistic atlases,
we construct vectors of class probabilities for each image voxel. By
defining new image similarity measures for distribution-valued images,
we show how the class probability images can be nonrigidly registered in
a variational framework. An experiment on nonrigid registration of MR
and CT full-body scans illustrates that the proposed technique outperforms
standard mutual information (MI) and normalized mutual information
(NMI) based registration techniques when measured in terms of
target registration error (TRE) of manually labeled fiducials.
17(260), 17th Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), April 2009 (poster)
There has recently been a growing interest in combining PET and MR. Attenuation correction (AC), which accounts for radiation attenuation properties of the tissue, is mandatory for quantitative PET. In the case of PET/MR the attenuation map needs to be determined from the MR image. This is intrinsically difficult as MR intensities are not related to the electron density information of the attenuation map. Using ultra-short echo (UTE) acquisition, atlas registration and machine learning, we present methods that allow prediction of the attenuation map based on the MR image both for brain and whole body imaging.
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems