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Multi-orientation geometric medical volumes segmentation using 3D multiresolution analysis

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Abstract

Medical images have a very significant impact in the diagnosing and treating process of patient ailments and radiology applications. For many reasons, processing medical images can greatly improve the quality of radiologists’ job. While 2D models have been in use for medical applications for decades, wide-spread utilization of 3D models appeared only in recent years. The proposed work in this paper aims to segment medical volumes under various conditions and in different axel representations. In this paper, we propose an algorithm for segmenting Medical Volumes based on Multiresolution Analysis. Different 3D volume reconstructed versions have been considered to come up with a robust and accurate segmentation results. The proposed algorithm is validated using real medical and Phantom Data. Processing time, segmentation accuracy of predefined data sets and radiologist’s opinions were the key factors for methods validations.

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Authors and Affiliations

  1. Department of Computer Science, Faculty of Science and IT, Al-Zaytoonah University of Jordan, Amman, Jordan

    Shadi AlZu’bi, Mohammed Elbes & Tarek Kanan

  2. Department of Computer Science, Jordan University of Science and Technology, Irbid, Jordan

    Yaser Jararweh

  3. Department of Mathematics, Faculty of Science and IT, Al-Zaytoonah University of Jordan, Amman, Jordan

    Hassan Al-Zoubi

  4. Department of Computer Engineering, National Institute of Technology Kurukshetra, Kurukshetra, India

    Brij Gupta

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  1. Shadi AlZu’bi
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AlZu’bi, S., Jararweh, Y., Al-Zoubi, H. et al. Multi-orientation geometric medical volumes segmentation using 3D multiresolution analysis. Multimed Tools Appl 78, 24223–24248 (2019). https://doi.org/10.1007/s11042-018-7003-4

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