Document Type
Poster Session
Department
Engineering
Faculty Mentor
Asheesh Lanba, PhD
Abstract
Automated image segmentation tools allow for the identification and quantification of biological features observed in cross-sectional images. This research analyzes the use of a pixel classification technique to define and quantify xylem conduits in plants. The images used for segmentation were obtained via laser ablation tomography (LATscan). Using open-source automated image segmentation software, we produce segmentations of vascular features in several plant species. The resulting segmentations allow us to run a count function, quantifying the area and count of xylem conduits. This quantification provides insight into the constitution of the plants as the xylem provides both mechanical structure and water delivery upward to sites of photosynthesis. Additionally, because growth rings are evident in the images, xylem conduit quantity may be seen with respect to age. This processing methodology will drastically increase the information available to crop scientists, allowing them to improve crop performance.
Open Access?
1
Quantifying Vascular Features in Plants Using Automated Image Segmentation
Automated image segmentation tools allow for the identification and quantification of biological features observed in cross-sectional images. This research analyzes the use of a pixel classification technique to define and quantify xylem conduits in plants. The images used for segmentation were obtained via laser ablation tomography (LATscan). Using open-source automated image segmentation software, we produce segmentations of vascular features in several plant species. The resulting segmentations allow us to run a count function, quantifying the area and count of xylem conduits. This quantification provides insight into the constitution of the plants as the xylem provides both mechanical structure and water delivery upward to sites of photosynthesis. Additionally, because growth rings are evident in the images, xylem conduit quantity may be seen with respect to age. This processing methodology will drastically increase the information available to crop scientists, allowing them to improve crop performance.
