7 research outputs found

    Multigrid methods and automatic segmentation: an application to CT images of the liver

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    We consider a segmentation problem which arises in medical imaging and liver surgery. The model problem is based on an active contour without edges technique formulated in a level set dictionary. Previous work indicates that a feasible solution can be obtained solving the gradient descent equation associated to the original minimization problem but the convergence of the algorithm is too slow for practical clinical purposes. Here, we study the implementation of multigrid methods to the elliptic problem and the numerical results are compared with the parabolic approach

    Spatiotemporal alignment of in utero BOLD-MRI series

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    Purpose: To present a method for spatiotemporal alignment of in-utero magnetic resonance imaging (MRI) time series acquired during maternal hyperoxia for enabling improved quantitative tracking of blood oxygen level-dependent (BOLD) signal changes that characterize oxygen transport through the placenta to fetal organs. Materials and Methods: The proposed pipeline for spatiotemporal alignment of images acquired with a single-shot gradient echo echo-planar imaging includes 1) signal nonuniformity correction, 2) intravolume motion correction based on nonrigid registration, 3) correction of motion and nonrigid deformations across volumes, and 4) detection of the outlier volumes to be discarded from subsequent analysis. BOLD MRI time series collected from 10 pregnant women during 3T scans were analyzed using this pipeline. To assess pipeline performance, signal fluctuations between consecutive timepoints were examined. In addition, volume overlap and distance between manual region of interest (ROI) delineations in a subset of frames and the delineations obtained through propagation of the ROIs from the reference frame were used to quantify alignment accuracy. A previously demonstrated rigid registration approach was used for comparison. Results: The proposed pipeline improved anatomical alignment of placenta and fetal organs over the state-of-the-art rigid motion correction methods. In particular, unexpected temporal signal fluctuations during the first normoxia period were significantly decreased (P < 0.01) and volume overlap and distance between region boundaries measures were significantly improved (P < 0.01). Conclusion: The proposed approach to align MRI time series enables more accurate quantitative studies of placental function by improving spatiotemporal alignment across placenta and fetal organs.National Institutes of Health (NIH) . Grant Numbers: U01 HD087211 , R01 EB017337 Consejeria de Educacion, Juventud y Deporte de la Comunidad de Madrid (Spain) through the Madrid-MIT M+Vision Consortium

    The interplay between functioning problems and symptoms in first episode of psychosis: an approach from network analysis

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    The relationship between psychotic symptoms and global measures of functioning has been widely studied. No previous study has assessed so far the interplay between specific clinical symptoms and particular areas of functioning in first-episode psychosis (FEP) using network analysis methods. A total of 191 patients with FEP (age 24.45 ± 6.28 years, 64.9% male) participating in an observational and longitudinal study (AGES-CM) comprised the study sample. Functioning problems were assessed with the WHO Disability Assessment Schedule (WHODAS), whereas the Positive and Negative Syndrome Scale (PANSS) was used to assess symptom severity. Network analysis were conducted with the aim of analysing the patterns of relationships between the different dimensions of functioning and PANSS symptoms and factors at baseline. According to our results, the most important nodes were “conceptual disorganization”, “emotional withdrawal”, “lack of spontaneity and flow of conversation”, “delusions”, “unusual thought content”, “dealing with strangers” and “poor rapport”. Our findings suggest that these symptoms and functioning dimensions should be prioritized in the clinical assessment and management of patients with FEP. These areas may also become targets of future early intervention strategies, so as to improve quality of life in this populationThis work was supported by the Madrid Regional Government (R&D activities in Biomedicine (grant number S2017/BMD-3740 - AGES-CM 2-CM)) and Structural Funds of the European Union. Ana Izquierdo’s work is supported by the PFIS predoctoral program (FI17/00138) from the Instituto de Salud Carlos III (Spain) and co-funded by the European Union (ERDF/ESF, "A way to make Europe”/ “Investing in your future”) and The Biomedical Research Foundation of La Princesa University Hospital. Angela Ib´a˜nez thanks the support of CIBERSAM and of the Spanish Ministry of Science, Innovation and Universities. Instituto de Salud Carlos III (PI16/00834 and PI19/01295) co-financed by ERDF Funds from the European Commission. Covadonga M. Díaz-Caneja holds a Juan Rod´es Grant from Instituto de Salud Carlos III (JR19/00024). Celso Arango was supported by the Spanish Ministry of Science and Innovation. Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012, PI19/ 024), co-financed by ERDF Funds from the European Commission, “A way of making Europe”, CIBERSAM. Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds. European Union Seventh Framework Program under grant agreements FP7-4-HEALTH-2009-2.2.1-2-241909 (Project EU-GEI), FP7- HEALTH- 2013-2.2.1-2-603196 (Project PSYSCAN) and FP7- HEALTH-2013- 2.2.1-2-602478 (Project METSY); and European Union H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking (grant agreement No 115916, Project PRISM, and grant agreement No 777394, Project AIMS-2-TRIALS), Fundaci´on Familia Alonso, Fundaci´on Alicia Koplowitz and Fundaci´on Mutua Madrile˜n

    On innovation and the impact of research

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    On innovation and the impact of research

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    H-EM: An algorithm for simultaneous cell diameter and intensity quantification in low-resolution imaging cytometry.

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    Fluorescent cytometry refers to the quantification of cell physical properties and surface biomarkers using fluorescently-tagged antibodies. The generally preferred techniques to perform such measurements are flow cytometry, which performs rapid single cell analysis by flowing cells one-by-one through a channel, and microscopy, which eliminates the complexity of the flow channel, offering multi-cell analysis at a lesser throughput. Low-magnification image-based cytometers, also called "cell astronomy" systems, hold promise of simultaneously achieving both instrumental simplicity and high throughput. In this magnification regime, a single cell is mapped to a handful of pixels in the image. While very attractive, this idea has, so far, not been proven to yield quantitative results of cell-labeling, mainly due to the poor signal-to-noise ratio present in those images and to partial volume effects. In this work we present a cell astronomy system that, when coupled with custom-developed algorithms, is able to quantify cell intensities and diameters reliably. We showcase the system using calibrated MESF beads and fluorescently stained leukocytes, achieving good population identification in both cases. The main contribution of the proposed system is in the development of a novel algorithm, H-EM, that enables inter-cluster separation at a very low magnification regime (2x). Such algorithm provides more accurate brightness estimates than DAOSTORM when compared to manual analysis, while fitting cell location, brightness, diameter, and background level concurrently. The algorithm first performs Fisher discriminant analysis to detect bright spots. From each spot an expectation-maximization algorithm is initialized over a heterogeneous mixture model (H-EM), this algorithm recovers both the cell fluorescence and diameter with sub-pixel accuracy while discriminating the background noise. Finally, a recursive splitting procedure is applied to discern individual cells in cell clusters

    Early perfusion changes in multiple sclerosis patients as assessed by MRI using arterial spin labeling

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    Background Gadolinium-perfusion magnetic resonance (MR) identifies gray matter abnormalities in early multiple sclerosis (MS), even in the absence of structural differences. These perfusion changes could be related to the cognitive disability of these patients, especially in the working memory. Arterial spin labeling (ASL) is a relatively recent perfusion technique that does not require intravenous contrast, making the technique especially attractive for clinical research. Purpose To verify the perfusion alterations in early MS, even in the absence of cerebral volume changes. To introduce the ASL sequence as a suitable non-invasive method in the monitoring of these patients. Material and Methods Nineteen healthy controls and 28 patients were included. The neuropsychological test EDSS and SDMT were evaluated. Cerebral blood flow and bolus arrival time were collected from the ASL study. Cerebral volume and cortical thickness were obtained from the volumetric T1 sequence. Spearman’s correlation analyzed the correlation between EDSS and SDMT tests and perfusion data. Differences were considered significant at a level of P < 0.05. Results Reduction of the cerebral blood flow and an increase in the bolus arrival time were found in patients compared to controls. A negative correlation between EDSS and thalamus transit time, and between EDSS and cerebral blood flow in the frontal cortex, was found. Conclusion ASL perfusion might detect changes in MS patients even in absent structural volumetric changes. More longitudinal studies are needed, but perfusion parameters could be biomarkers for monitoring these patients.Sin financiaciónNo data 2019UE
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