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Automatic lattice detection in near-regular histology array images

8 years 8 months ago
Automatic lattice detection in near-regular histology array images
Near-regular texture (NRT), denoting deviations from otherwise symmetric wallpaper patterns, is commonly observable in the real world. Existing lattice detection algorithms capture the underlying lattice of an NRT pattern and all of its individual texels, facilitating an automated analysis of NRT. Many real world images, as in those of zebrafish larval histology arrays, depart significantly from regularity and challenge the current state of the art wallpaper group theory-based lattice detection methods. We propose an alternative 2D lattice detection algorithm that exploits translation and reflection symmetries and specific imaging cues. By outperforming existing methods on histology array images, our algorithm leads us towards complete automation of high-throughput histological image processing while broadening the spectrum of NRT computation.
Brian A. Canada, Georgia K. Thomas, Keith C. Cheng
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICIP
Authors Brian A. Canada, Georgia K. Thomas, Keith C. Cheng, James Ze Wang, Yanxi Liu
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