Boundary detection in MR image with brain tumor is an important image processiug technique applied in Radiology for 3D reconstruction. The nonhomogeneities density tissue of the brain with tumor can result in achieving the inaccurate location in any boundary detection algorithms. Recently, some studies using the contour deformable model with regional base technique, the performance is insuffici...

This paper presents an algorithm for finding edge-disjoint paths in a given plane grid bounded by two nested rectangles. A pair of vertices on the boundary of the same rectangle are designated as terminals for each of the paths. The number of terminals lying on each boundary vertex is determined by the degree of the boundary vertex. Every vertex of degree 2 has either 0 or 2 terminals lying on ...

Ellipse fitting for iris boundary is an important step in eye gaze estimation and iris recognition applications. In most of the proposed algorithms only the edge image is used for ellipse fitting. In these algorithms, the undesired edges may lead to erroneous iris ellipse. In this paper, we propose a novel algorithm to ellipse fitting for iris boundary which uses gray and edge images simultaneo...

PURPOSE In iterative positron emission tomography (PET) image reconstruction, the statistical variability of the PET data precorrected for random coincidences or acquired in sufficiently high count rates can be properly approximated by a Gaussian distribution, which can lead to a penalized weighted least-squares (PWLS) cost function. In this study, the authors propose a proximal preconditioned ...

We study the tight-binding model for a graphene tube with perimeter N threaded by a magnetic field. We show exactly that this model has different nontrivial topological phases as the flux changes. The winding number, as an indicator of topological quantum phase transition (QPT) fixes at N/3 if N/3 equals to its integer part [N/3], otherwise it jumps between [N/3] and [N/3] + 1 periodically as t...

In the Digital Image Processing, edge detection playing a vital role. An edge is the boundary between an object and the background, and indicates the boundary between overlapping objects. Artificial Neural Network, inspired by the way of biological nervous systems such as human brains process information and it is an information processing system which contains a large number of highly intercon...

This paper describes an approach to construct unstructured tetrahedral and hexahedral meshes for a domain with multiple materials. We have developed an octree-based isocontouring method to construct unstructured 3D meshes for a single material domain. Based on it, we analyze each material change edge instead of sign change edge to figure out interfaces between two materials, and mesh each mater...

Semantic boundary and edge detection aims at simultaneously detecting object edge pixels in images and assigning class labels to them. Systematic training of predictors for this task requires the labeling of edges in images which is a particularly tedious task. We propose a novel strategy for solving this task in an almost zero-shot manner by relying on conventional whole image neural net class...

Diagnostics in medicine is often based on analysis of medical images. Extraction of the shape of objects is one basic step for further image analysis. It consists of two steps: (i) edge detection and (ii) contour recovery based on the detected edge points. In this paper we focus on the second step. We describe the boundary of an object by trigonometric polynomials and present a fast and robust ...

Medical image segmentation plays a crucial role in identifying the shape and structure of human anatomy. The most widely used image segmentation algorithms are edge-based and typically rely on the intensity inhomogeneity of the image at the edges, which often fail to provide accurate segmentation results. This paper proposes a boundary detection technique for segmenting the hippocampus (the sub...