Fig 1.
Overview of image analysis pipeline.
(Upper panel) schematic representations of the stages of image analysis. Text boxes contain brief descriptions, see text for more detail, roman numerals correspond to steps in the workflow. Arrows show where data is extracted from the image for analysis. (A) Orthogonal projection of whitened 18 dimensional data extracted from the image. Colouring is made on result of clustering, with crosses and ellipses represent centres and covariances of the identified clusters. (B) Example representation of pixel colour density in the 3D colour space, showing identification of vectors corresponding to in situ stain, pigmented and un-pigmented embryo, used to identify regions of the embryo expressing the gene in question. (C) Example histogram of stain distribution. Data modelled as mixture of two Gaussians. The threshold is the smallest of mu + 2*sigma of the two components; it is represented as a solid green line. Dashed red lines represent range of values [.25, .67] the threshold is allowed to take.
Fig 2.
Graphical depiction of image analysis workflow for selected images with different shape embryos and a range of different background colours and textures.
Images show that embryo detection and stain colour analysis is effective independently of a wide range of variation in image background and embryo characteristics. All images were analysed without changing initial parameters. Note image (d) where even the human eye struggles to distinguish the upper border of the embryo from the background.
Table 1.
Validation of image classification and embryo detection algorithms: Identification of non-subjective errors through visual inspection of 2000 randomly selected images.
Image classification: was the image correctly classified as cleared or un-cleared? Background segmentation: was the background component identified correctly? Embryo region selection: did the connected region selected correspond to the embryo? Incomplete embryo detection: were embryos touching the image edge correctly identified as such?
Table 2.
Validation of the algorithm output.
Two WISH experts marked each of 200 processed images as good, intermediate or bad (1.0, 0.5 or 0.0) on three potentially subjective qualities: whether the embryo outline had been captured correctly, whether the stained regions were delineated correctly, and whether the pigmented regions were delineated correctly. For each quality we correlated the experts’ scores over all 200 images.
Fig 3.
Rational selection of representative images to reduce redundancy.
Unsorted images from a large collection for a given gene/development stage are first classified into cleared (grey background) and un-cleared (orange/red background) images. Embryo boundaries were detected within the image and embryo pixel colours analysed to yield predicted in situ stain, pigmentation or unmarked embryo. Embryos with predicted outline touching the image border were excluded (unless the outline in all images in the group touched the border). Images were sorted within groups by stain content for selection, and cropped for display where needed. (A) Lateral view images, NF stage 20+. (B) Quasi-spherical development stages (up to NF stage 20): images are clustered according to expression pattern similarity under rotational and other transformations (see also Fig 4), and the most stained image is selected from each well-separated group.
Fig 4.
Simplified example of spherical stage image similarity clustering.
Early development stages are routinely photographed from different directions to maximise information about the expression pattern. Reference and comparison images for the same gene and stage are compared under multiple transformations (scale, rotation, shear) to identify the set of transformations that minimises their dissimilarity. Here we see that a 91.5o rotation and a 1.01 scaling suggest the most likely transformation between these two images. All images from the same gene and stage are compared with each other to identify images from (probably) the same view-point. See also Fig 3B.
Fig 5.
Developmental progression of expression for selected genes prdm1, ank1, and hoxb3 during Xenopus embryo development.
This is the result of applying our suite of image analysis tools to (in this case) the 334 original images for these three genes, and reducing them to a representative set of 65 images, including multiple views of expression patterns from the early spherical stages (pre-Stage 22).