ABSTRACT
Are the answers to biological questions obtained via live fluorescence microscopy substantially affected by phototoxicity? Although a single set of standards for assessing phototoxicity cannot exist owing to the breadth of samples and experimental questions associated with biological imaging, we need quantitative, practical assessments and reporting standards to ensure that imaging has a minimal impact on observed biological processes and sample health. Here we discuss the problem of phototoxicity in biology and suggest guidelines to improve its reporting and assessment.
Subject(s)
Cell Proliferation/radiation effects , DNA Damage , Dermatitis, Phototoxic/etiology , Light , Microscopy, Fluorescence/methods , Animals , Chlorocebus aethiops , Dermatitis, Phototoxic/genetics , Dermatitis, Phototoxic/pathology , Free Radicals/metabolism , Light/adverse effects , Vero CellsABSTRACT
Blobs and curves occur everywhere in plant bioimaging: from signals of fluorescence-labelled proteins, through cytoskeletal structures, nuclei staining and cell extensions such as root hairs. Here we look at the problem of colocalisation of blobs with blobs (protein-protein colocalisation) and blobs with curves (organelle-cytoskeleton colocalisation). This article demonstrates a clear quantitative alternative to pixel-based colocalisation methods and, using object-based methods, can quantify not only the level of colocalisation but also the distance between objects. Included in this report are computational algorithms, biological experiments and guidance for those looking to increase their use of computationally-based and quantified analysis of bioimages.
ABSTRACT
This paper presents an algorithm for reducing speckle noise from optical coherence tomography (OCT) images using an artificial neural network (ANN) algorithm. The noise is modeled using Rayleigh distribution with a noise parameter, sigma, estimated by the ANN. The input to the ANN is a set of intensity and wavelet features computed from the image to be processed, and the output is an estimated sigma value. This is then used along with a numerical method to solve the inverse Rayleigh function to reduce the noise in the image. The algorithm is tested successfully on OCT images of Drosophila larvae. It is demonstrated that the signal-to-noise ratio and the contrast-to-noise ratio of the processed images are increased by the application of the ANN algorithm in comparison with the respective values of the original images.
