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imcontour  (MathWorks Inc)


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    MathWorks Inc imcontour
    Imcontour, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/imcontour/us11704765-1198-10-12
    Average 90 stars, based on 1 article reviews
    imcontour - by Bioz Stars, 2026-09
    90/100 stars

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    Software:

    Article Title: Additive manufacture of custom radiation dosimetry phantoms: An automated method compatible with commercial polymer 3D printers
    Article Snippet: Contents lists available at ScienceDirect Materials and Design j ourna l homepage: www.e lsev ie r .com/ locate / jmad Additive manufacture of custom radiation dosimetry phantoms: An automated method compatible with commercial polymer 3D printers Martin Leary a,⁎, Tomas Kron b,c, Cameron Keller a, Rick Franich c, Peta Lonski b,c, Aleksandar Subic d, Milan Brandt a a RMIT Centre for Additive Manufacture, Innovative Manufacturing Research Group (Medical Manufacturing), RMIT University, Melbourne, Australia b Peter MacCallum Cancer Centre, Melbourne, Australia c School of Applied Sciences, RMIT University, Melbourne, Australia d Swinburne Research, Swinburne University of Technology, Australia ⁎ Corresponding author.. E-mail address: martin.leary@rmit.edu.au (M. Leary). http://dx.doi.org/10.1016/j.matdes.2015.07.052 0264-1275/© 2015 Elsevier Ltd. All rights reserved. a b s t r a c t a r t i c l e i n f o Article history: Received 27 March 2015 Received in revised form 9 July 2015 Accepted 10 July 2015 Available online 21 July 2015 Keywords: Contrast detail phantom Design for Additive Manufacture Expert systems Radiotherapy Treatment verification Anthropomorphic phantom Personalised medicine There exist significant opportunities for the improvement of radiation therapy procedures by the development of custom dosimetry phantoms for training, quality assurance, and clinical research.. Additive manufacture enables customphantommanufacture, however there exist technical challenges, namely the lack of specialisedmaterials to mimic radiation interaction properties of natural materials, and a lack of automated methods to reduce the manual effort required to convert medical scan data into an additive component.

    other:

    Article Title: Artwork generated to convey digital messages, and methods/apparatuses for generating such artwork
    Article Snippet: One example of this type of image processing routine is imcontour in MatLab software from MathWorks.



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    Segmentation results of our adversarial adaption model: confocal domain to light sheet domain (left) and light sheet domain to confocal domain (right). The red contour obtained using <t>MATLAB</t> <t>imcontour</t> function on the binary segmentation predictions. The bottom row shows the zoomed results.
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    Segmentation results of our adversarial adaption model: confocal domain to light sheet domain (left) and light sheet domain to confocal domain (right). The red contour obtained using <t>MATLAB</t> <t>imcontour</t> function on the binary segmentation predictions. The bottom row shows the zoomed results.
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    MathWorks Inc matlab routine 'imcontour
    Segmentation results of our adversarial adaption model: confocal domain to light sheet domain (left) and light sheet domain to confocal domain (right). The red contour obtained using <t>MATLAB</t> <t>imcontour</t> function on the binary segmentation predictions. The bottom row shows the zoomed results.
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    Image Search Results


    Segmentation results of our adversarial adaption model: confocal domain to light sheet domain (left) and light sheet domain to confocal domain (right). The red contour obtained using MATLAB imcontour function on the binary segmentation predictions. The bottom row shows the zoomed results.

    Journal: Bioinformatics and Biomedical Engineering : 7th International Work-Conference, IWBBIO 2019, Granada, Spain, May 8-10, 2019, Proceedings, Parts I and II. IWBBIO (Conference) (7th : 2019 : Granada, Spain)

    Article Title: Cross Modality Microscopy Segmentation via Adversarial Adaptation

    doi: 10.1007/978-3-030-17935-9_42

    Figure Lengend Snippet: Segmentation results of our adversarial adaption model: confocal domain to light sheet domain (left) and light sheet domain to confocal domain (right). The red contour obtained using MATLAB imcontour function on the binary segmentation predictions. The bottom row shows the zoomed results.

    Article Snippet: The red contour obtained using MATLAB imcontour function on the binary segmentation predictions.

    Techniques: