C3VFC: A Method for Tracing and Quantification of Microglia in 3D Temporal Images

Automatic glia reconstruction is essential for the dynamic analysis of microglia motility and morphology, notably so in research on neurodegenerative diseases. In this paper, we propose an automatic 3D tracing algorithm called C3VFC that uses vector field convolution to find the critical points along the centerline of an object and trace paths that traverse back to the soma of every cell in an image. The solution provides detection and labeling of multiple cells in an image over time, leading to multi-object reconstruction. The reconstruction results can be used to extract bioinformatics from temporal data in different settings. The C3VFC reconstruction results found up to a 53% improvement on the next best performing state-of-the-art tracing method. C3VFC achieved the highest accuracy scores, in relation to the baseline results, in four of the five different measures: Entire structure average, the average bi-directional entire structure average, the different structure average, and the percentage of different structures.

Segmentation of Cotton Leaf Images using Parametric Deformable Model

In this paper, the segmentation of cotton leaves from the complex background has been carried out using deformable model. In order to segment, a database of about 300 cotton leaves image was developed. The collected images were resized to 256x256 size. The resized image has been segmented using Adaptive Diffusion Flow (ADF) model. The ADF model has been obtained by replacing the smoothening energy term of gradient vector flow model with active hyper surface harmonic minimal function used to keep away from weak edges leakage. The infinite Laplace function is used to move the deformable model into narrow concave regions. Further, the developed model has been compared with the gradient vector flow and vector field convolution segmentation methods in terms of number of iterations, time taken for segmentation and various performance parameters namely precision, recall, Manhattan, Jaccard, Dice. From the results, it is concluded that the adaptive diffusion flow method is faster and performance parameters are better than the Gradient Vector Flow (GVF) and Vector Field Convolution (VFC) methods.

Vector Field Convolution-Based B-Spline Deformation Model for 3D Segmentation of Cartilage in MRI

In this paper, a novel 3D vector field convolution (VFC)-based B-spline deformation model is proposed for accurate and robust cartilage segmentation. Firstly, the anisotropic diffusion method is utilized for noise reduction, and the Sinc interpolation method is employed for resampling. Then, to extract the rough cartilage, features derived from