Sentence examples for border detection method from inspiring English sources

This paper proposes an automatic border detection method which determines the optimal color channels and performs hybrid thresholding to detect the lesion borders.

The hybrid border detection method is tested on a set of 85 dermoscopy images with two sets of ground truth using various metrics including accuracy, precision, sensitivity, specificity, and border error.

Although numerous border detection methods have been developed, few studies have focused on determining the optimal color channels for border detection in dermoscopy images.

It is shown to be highly competitive with three state-of-the-art border detection methods and potentially faster, since it mainly involves scalar processing as opposed to vector processing performed in the other methods.

The automatic transcript border detection methods, statistical models and operon organization pipeline that we have described could be widely applied to RNA-seq studies in other bacteria.

Regarding the concerns of subjectivity and consistency of the manually generated borders, 5 6 many automatic border detection methods have been developed, such as the JSEG algorithm, contrast enhancement and clustering algorithms, with different evaluation metrics.

Cell borders are fuzzy, therefore thresholding is preferred to edge detection methods for segmentation.

The speckle tracking, border detection and model fitting methods are implemented in C++ using open-source tools.

As seen in Figure 5, that degrades efficiency of the method for border detection in lesions since border regions have similar features with noise.

Advanced methods for improving or extracting more information from image data include time gain compensation (TGC), compounding, border detection and three-dimensional visualization methods.

Perhaps contrast-enhanced 3D volumetric quantification could be a method for better border detection as shown in human medicine [ 32].