Leaf Asymmetry as a Developmental Constraint Imposed by Auxin-Dependent Phyllotactic Patterning

In a majority of species, leaf development is thought to proceed in a bilaterally symmetric fashion without systematic asymmetries. This is despite the left and right sides of an initiating primordium occupying niches that differ in their distance from sinks and sources of auxin. Here, we revisit an existing model of auxin transport sufficient to recreate spiral phyllotactic patterns and find previously overlooked asymmetries between auxin distribution and the centers of leaf primordia. We show that it is the direction of the phyllotactic spiral that determines the side of the leaf these asymmetries fall on. We empirically confirm the presence of an asymmetric auxin response using a DR5 reporter and observe morphological asymmetries in young leaf primordia. Notably, these morphological asymmetries persist in mature leaves, and we observe left-right asymmetries in the superficially bilaterally symmetric leaves of tomato (Solanum lycopersicum) and Arabidopsis thaliana that are consistent with modeled predictions. We further demonstrate that auxin application to a single side of a leaf primordium is sufficient to recapitulate the asymmetries we observe. Our results provide a framework to study a previously overlooked developmental axis and provide insights into the developmental constraints imposed upon leaf morphology by auxin-dependent phyllotactic patterning.

Ruler Based Automatic C-Arm Image Stitching Without Overlapping Constraint

In this paper, we propose a new method for stitching multiple fluoroscopic images taken by a C-arm instrument. We employ an X-ray radiolucent ruler with numbered graduations while acquiring the images, and the image stitching is based on detecting and matching ruler parts in the images to the corresponding parts of a virtual ruler. To achieve this goal, we first detect the regular spaced graduations on the ruler and the numbers. After graduation labeling, for each image, we have the location and the associated number for every graduation on the ruler. Then, we initialize the panoramic X-ray image with the virtual ruler, and we “paste” each image by aligning the detected ruler part on the original image, to the corresponding part of the virtual ruler on the panoramic image. Our method is based on ruler matching but without the requirement of matching similar feature points in pairwise images, and thus, we do not necessarily require overlap between the images. We tested our method on eight different datasets of X-ray images, including long bones and a complete spine. Qualitative and quantitative experiments show that our method achieves good results.