Gold Nanoparticles Cause Radiosensitization in 4T1 Cells by Inhibiting DNA Double Strand Break Repair: Single Cell Comparisons of DSB Formation and γH2AX Expression.

Metal nanoparticles sensitize cancers to radiotherapy however their mechanisms of action are complex. The conceptual inspiration arose from theories of physical dose deposition however various chemical and biological factors have also been identified. Interpretation of data has been limited by challenges in measuring true DNA damage compared to DNA damage repair factors.

Correction to: Detection and analysis of wheat spikes using Convolutional Neural Networks.

[This corrects the article DOI: 10.1186/s13007-018-0366-8.].

Detection and analysis of wheat spikes using Convolutional Neural Networks.

Background: Field phenotyping by remote sensing has received increased interest in recent years with the possibility of achieving high-throughput analysis of crop fields. Along with the various technological developments, the application of machine learning methods for image analysis has enhanced the potential for quantitative assessment of a multitude of crop traits. For wheat breeding purposes, assessing the production of wheat spikes, as the grain-bearing organ, is a useful proxy measure of grain production.

Land-based crop phenotyping by image analysis: consistent canopy characterization from inconsistent field illumination.

Background: One of the main challenges associated with image-based field phenotyping is the variability of illumination. During a single day's imaging session, or between different sessions on different days, the sun moves in and out of cloud cover and has varying intensity. How is one to know from consecutive images alone if a plant has become darker over time, or if the weather conditions have simply changed from clear to overcast? This is a significant problem to address as colour is an important phenotypic trait that can be measured automatically from images.

Land-based crop phenotyping by image analysis: Accurate estimation of canopy height distributions using stereo images.

In this paper we report on an automated procedure to capture and characterize the detailed structure of a crop canopy by means of stereo imaging. We focus attention specifically on the detailed characteristic of canopy height distribution-canopy shoot area as a function of height-which can provide an elaborate picture of canopy growth and health under a given set of conditions. We apply the method to a wheat field trial involving ten Australian wheat varieties that were subjected to two different fertilizer treatments.

A Hybrid Approach for Improving Image Segmentation: Application to Phenotyping of Wheat Leaves.

In this article we propose a novel tool that takes an initial segmented image and returns a more accurate segmentation that accurately captures sharp features such as leaf tips, twists and axils. Our algorithm utilizes basic a-priori information about the shape of plant leaves and local image orientations to fit active contour models to important plant features that have been missed during the initial segmentation. We compare the performance of our approach with three state-of-the-art segmentation techniques, using three error metrics.

RootAnalyzer: A Cross-Section Image Analysis Tool for Automated Characterization of Root Cells and Tissues.

The morphology of plant root anatomical features is a key factor in effective water and nutrient uptake. Existing techniques for phenotyping root anatomical traits are often based on manual or semi-automatic segmentation and annotation of microscopic images of root cross sections. In this article, we propose a fully automated tool, hereinafter referred to as RootAnalyzer, for efficiently extracting and analyzing anatomical traits from root-cross section images.