Ulas Bagci

  1. Ball-Scale Based Hierarchical Multi-Object Recognition in 3D Medical Images.

    Authors: Ulas Bagci, Jayaram K. Udupa, Xinjian Chen
    Subjects: Computer Vision and Pattern Recognition
    Abstract

    This paper investigates, using prior shape models and the concept of ball
    scale (b-scale), ways of automatically recognizing objects in 3D images without
    performing elaborate searches or optimization. That is, the goal is to place
    the model in a single shot close to the right pose (position, orientation, and
    scale) in a given image so that the model boundaries fall in the close vicinity
    of object boundaries in the image. This is achieved via the following set of
    key ideas: (a) A semi-automatic way of constructing a multi-object shape model
    assembly.

  2. The Influence of Intensity Standardization on Medical Image Registration.

    Authors: Ulas Bagci, Jayaram K. Udupa, Li Bai
    Subjects: Computer Vision and Pattern Recognition
    Abstract

    Acquisition-to-acquisition signal intensity variations (non-standardness) are
    inherent in MR images. Standardization is a post processing method for
    correcting inter-subject intensity variations through transforming all images
    from the given image gray scale into a standard gray scale wherein similar
    intensities achieve similar tissue meanings. The lack of a standard image
    intensity scale in MRI leads to many difficulties in tissue characterizability,
    image display, and analysis, including image segmentation.

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