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Titlebook: Abdominal Imaging. Computational and Clinical Applications; 5th International Wo Hiroyuki Yoshida,Simon Warfield,Michael W. Vannier Confere

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Stefan Henningsson,Gustav Normark Toppenberg a better performance over the existing MIND method on the DIR-Lab dataset as well as on abdominal MRI datasets albeit not significant. Ultimately, we will use the technique to quantify Crohn’s disease severity based on the relative contrast enhancement in registered images.
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Christian Bunse,Hans-Gerhard Grossutomated CADe scheme was used to detect lesion candidates in the images reconstructed at conventional 0.61-mm and at 0.10-mm SR image resolution. The proof-of-concept results indicate that the SR method has potential to reduce the number of FP CADe detections below that obtainable with the conventional CTC imaging technology.
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Building a Web Services Workflow,thod improved the fit of the PK model to clinical colorectal cancer cases, was stable for independent regions in the tumour, and showed improved localisation of the PK parameters. This demonstrates that personalised AIF estimation can lead to more accurate PK modelling.
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Anjani Kumar,Abhishek Mishra,Sanjeev Kumartour correspondences through a novel variational one-step deformable Iterative Closest Point (ICP) method. The proposed method compared favorably with classical ICP and Thin-Plate Spline Robust Point Matching (TPS-RPM) on several datasets.
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