Transforms and Operators for Directional Bioimage Analysis: A Survey

Abstract

We give a methodology-oriented perspective on directional image analysis and rotation-invariant processing. We review the state of the art in the field and make connections with recent mathematical developments in functional analysis and wavelet theory. We unify our perspective within a common framework using operators. The intent is to provide image-processing methods that can be deployed in algorithms that analyze biomedical images with improved rotation invariance and high directional sensitivity. We start our survey with classical methods such as directional-gradient and the structure tensor. Then, we discuss how these methods can be improved with respect to robustness, invariance to geometric transformations (with a particular interest in scaling), and computation cost. To address robustness against noise, we move forward to higher degrees of directional selectivity and discuss Hessian-based detection schemes. To present multiscale approaches, we explain the differences between Fourier filters, directional wavelets, curvelets, and shearlets. To reduce the computational cost, we address the problem of matching directional patterns by proposing steerable filters, where one might perform arbitrary rotations and optimizations without discretizing the orientation. We define the property of steerability and give an introduction to the design of steerable filters. We cover the spectrum from simple steerable filters through pyramid schemes up to steerable wavelets. We also present illustrations on the design of steerable wavelets and their application to pattern recognition.

Planar cell polarity-dependent and independent functions in the emergence of tissue-scale hair follicle patterns

“…1B,D). To visualize the local order and global pattern of the thousands of follicles across the entire dorsal surface of the body, tiled images of dorsal backskins were acquired and processed using OrientationJ to color-code individual follicles according to their directionality (Puspoki et al, 2016; Fig. 2).…”

Engineering Muscle Networks in 3D Gelatin Methacryloyl Hydrogels: Influence of Mechanical Stiffness and Geometrical Confinement

“…The distributions of myotube orientation within the hydrogel structures following in vitro culture was obtained by analyzing IF micrographs (MHC signal) with OrientationJ plugin (Püspöki et al, 2016). The plugin evaluates the orientation for every pixel of the image based on the structure tensor and provides an orientation distribution plot as an output.…”

Oblique illumination in microscopy: A quantitative evaluation

“…Note how all the selected OL filters provide a significant improvement for all selected indicators, including the response of an ideal observer given by the AQI measure that has shown an excellent performance as a no-reference quality measure, providing a high correlation with Mean Opinion Scores (MOS) of human observers. An additional measure of the degree of improvement obtained by the oblique light is given by the coherence image representation that can be interpreted as a combined measure of edgeness and orientation (Figure 4) [20]. Figure 5 presents an example of the use of OL and COL filters for improving contrast.…”