7 research outputs found

    Plenoptic Modeling of 3D Scenes with a Sensor-augmented Multi-Camera Rig

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    We propose a system for robust modeling and visualisation of complex outdoor scenes from multi-camera image sequences and additional sensor information. A camera rig with one or more fire-wire cameras is used in conjunction with a 3-axis rotation sensor to robustly obtain a calibration of the scene with an uncalibrated structure from motion approach. Dense depth maps are estimated with multi-viewpoint stereo and the scene is visualized from a plenoptic representation of the scene

    Distributed Realtime Interaction and Visualization System

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    A distributed realtime system for immersive visualization is presented which uses distributed interaction for control. We will focus on user tracking with fixed and pan-tilt-zoom cameras, synchronization of multiple interaction devices and distributed synchronized visualization. The system uses only standard hardware and standard network protocols. Furthermore for the realtime visualization we only use consumer graphics hardware

    Using AI and Gd-EOB-DTPA-enhanced MR imaging to assess liver function, comparing the MELIF score with the ALBI score

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    Abstract Monitoring disease progression is particularly important for determining the optimal treatment strategy in patients with liver disease. Especially for patients with diseases that have a reversible course, there is a lack of suitable tools for monitoring liver function. The development and establishment of such tools is very important, especially in view of the expected increase in such diseases in the future. Image-based liver function parameters, such as the T1 relaxometry-based MELIF score, are ideally suited for this purpose. The determination of this new liver function score is fully automated by software developed with AI technology. In this study, the MELIF score is compared with the widely used ALBI score. The ALBI score was used as a benchmark, as it has been shown to better capture the progression of less severe liver disease than the MELD and Child‒Pugh scores. In this study, we retrospectively determined the ALBI and MELIF scores for 150 patients, compared these scores with the corresponding MELD and Child‒Pugh scores (Pearson correlation), and examined the ability of these scores to discriminate between good and impaired liver function (AUC: MELIF 0.8; ALBI 0.77) and to distinguish between patients with and without cirrhosis (AUC: MELIF 0.83, ALBI 0.79). The MELIF score performed more favourably than the ALBI score and may also be suitable for monitoring mild disease progression. Thus, the MELIF score is promising for closing the gap in the available early-stage liver disease monitoring tools (i.e., identification of liver disease at a potentially reversible stage before chronic liver disease develops)

    Enhanced overexpression of hypoxia-related miRNA-210 in primary tumor of metastatic prostate cancer.

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    166 Background: miR-210 is a known transcriptional target of the hypoxia-responsive HIF-1α signaling pathway. However, the association between the expression of miR-210 and the tumor progression in prostate cancer (PCa) remains unclear. Methods: We isolated miRNA by miRNeasy FFPE kit (Qiagen, Hilden, Germany) from paraffin-embedded tissues of 87 prostate specimens with adenocarcinoma of the prostate cancer in different tumor stages, with high-grade prostatic intraepithelial neoplasia (HGPIN) and normal tissues. Organ-confined PCa was defined as PCa with pT2 tumor stage, Gleason score ≤ 7a and PSA level &lt; 10 ng/ml. PCa with pT3/4 or Gleason &gt; 7a was defined as advanced PCa. PCa with pN1 were considered as metastatic diseases. Additionally, 3 cases with castration-resistant prostate cancer (CRPC) were considered. Quantitative miR-210 expression data were acquired and analyzed using a real-time TaqMan-based PCR with the ABI Prism 7900HT (Life Technologies, Darmstadt, Germany). ANOVA and post hoc analysis according to Turkey were performed using SPSS 22 (IBM, Armonk, USA). For silico analysis, Diana tools were applied to determine target genes of miR-210 and related functions and pathways. All the statistical tests were two-sided, and the level of statistical significance was set at P &lt; 0.05. The small nuclear U6 RNA was used as an endogenous control. Results: ANOVA revealed significant differences in expression levels of miR-210 according to the tumor progression. Interestingly, organ-confined PCa showed the lowest expression level of miR-210 in our analysis. No sig. differences in miR-210 expression between normal tissues, HGPIN and organ-confined PCa and between advanced PCa, metastatic diseases and CRPC were observed. However, miR-210 expression was significantly higher in metastatic diseases and CRPC in comparison to organ-confined PCa. The silico analysis showed that genes regulated by miR-210 were associated with homologous recombination, non-homologous end-joining, the cell cycle regulation and synthesis of DNA. Conclusions: We observed an enhanced overexpression of hypoxia-related miRNA-210 in primary tumor of metastatic prostate cancer and CRPC in comparison to organ-confined PCa. </jats:p

    MELIF, a Fully Automated Liver Function Score Calculated from Gd-EOB-DTPA-Enhanced MR Images: Diagnostic Performance vs. the MELD Score

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    In the management of patients with chronic liver disease, the assessment of liver function is essential for treatment planning. Gd-EOB-DTPA-enhanced MRI allows for both the acquisition of anatomical information and regional liver function quantification. The objective of this study was to demonstrate and evaluate the diagnostic performance of two fully automatically generated imaging-based liver function scores that take the whole liver into account. T1 images from the native and hepatobiliary phases and the corresponding T1 maps from 195 patients were analyzed. A novel artificial-intelligence-based software prototype performed image segmentation and registration, calculated the reduction rate of the T1 relaxation time for the whole liver (rrT1(liver)) and used it to calculate a personalized liver function score, then generated a unified score-the MELIF score-by combining the liver function score with a patient-specific factor that included weight, height and liver volume. Both scores correlated strongly with the MELD score, which is used as a reference for global liver function. However, MELIF showed a stronger correlation than the rrT1(liver) score. This study demonstrated that the fully automated determination of total liver function, regionally resolved, using MR liver imaging is feasible, providing the opportunity to use the MELIF score as a diagnostic marker in future prospective studies
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