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Proceedings ArticleDOI

Medical Images Edge Detection Based on Mathematical Morphology

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TLDR
A novel mathematical morphological edge detection algorithm is proposed to detect the edge of lungs CT image with salt-and-pepper noise and the experimental results show that the proposed algorithm is more efficient for medical image denoising and edge detection than the usually used template-based edge detection algorithms and general morphologicalEdge detection algorithms.
Abstract
Medical images edge detection is an important work for object recognition of the human organs and it is an important pre-processing step in medical image segmentation and 3D reconstruction. Conventionally, edge is detected according to some early brought forward algorithms such as gradient-based algorithm and template-based algorithm, but they are not so good for noise medical image edge detection. In this paper, basic mathematical morphological theory and operations are introduced at first, and then a novel mathematical morphological edge detection algorithm is proposed to detect the edge of lungs CT image with salt-and-pepper noise. The experimental results show that the proposed algorithm is more efficient for medical image denoising and edge detection than the usually used template-based edge detection algorithms and general morphological edge detection algorithms

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Citations
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Mathematical Morphological Edge Detection for Different Applications :A Comparative Study

TL;DR: In this paper, the mathematical morphological edge detection results were compared with traditional edge detection method and the results showed that mathematical morphology is a new technique for edge detection, it is a theory and technique for analysis and processing of geometrical structures based on set theory.
Journal ArticleDOI

Combining Clustering, Morphology and Metaheuristic Optimization Technique for Segmentation of Breast Ultrasound Images to Detect Tumors

TL;DR: A framework which combines morphological operations and metaheuristic optimization technique with clustering method for the precise segmentation of breast tumours using ultrasound images is proposed in this study and the values evidenced that the proposed method distinctly outperforms other methods.
Journal ArticleDOI

Algorithm for the precise detection of single and cluster cells in microfluidic applications.

TL;DR: The method developed in the present study is the first image processing algorithm designed to be flexible in use and provides the scientific community with a very accurate imaging algorithm in the field of microfluidic applications.
Journal ArticleDOI

Fuzzy mathematical morphology using triangular operators and its application to images

TL;DR: A fuzzy morphological approach to detect the edges of real time images in order to preserve their features and it is observed that the gradient image using fuzzy morphology with Hamacher t-norm and t-conorm performs better in noisy environment.

Edge Detection of Satellite Images:A Comparative Study

TL;DR: An improved method for edge detection (lower constructor with laplacian operator with morphological operator) has compared withmorphological operator, specifically for the edge detection of satellite images.
References
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Book

Image Analysis and Mathematical Morphology

Jean Serra
TL;DR: This invaluable reference helps readers assess and simplify problems and their essential requirements and complexities, giving them all the necessary data and methodology to master current theoretical developments and applications, as well as create new ones.
Journal ArticleDOI

Detection of Intensity Changes with Subpixel Accuracy Using Laplacian-Gaussian Masks

TL;DR: A system that takes a gray level image as input, locates edges with subpixel accuracy, and links them into lines and notes that the zero-crossings obtained from the full resolution image using a space constant ¿ for the Gaussian, are very similar, but the processing times are very different.
Journal ArticleDOI

Morphologic edge detection

TL;DR: The blur-minimum morphologic edge operator is defined, its inherent noise sensitivity is less than the dilation or the erosion residue operators, and it is less computationally complex than the facet edge operator.
Journal ArticleDOI

A new algorithm for image noise reduction using mathematical morphology

TL;DR: The paper describes the MIC algorithm in detail, discusses the effects of parametric variations, presents the results of a noise analysis and shows a number of examples of its use, including the removal of scanner noise.
Journal ArticleDOI

Differential morphology and image processing

TL;DR: The analysis of the multiscale morphological PDEs and of the eikonal PDE solved via weighted distance transforms are viewed as a unified area in nonlinear image processing, which is called differential morphology, and its potential applications to image processing and computer vision are discussed.
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