A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of thresholding techniques
Computer Vision, Graphics, and Image Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised texture segmentation using Gabor filters
Pattern Recognition
Texture Segmentation Using Fractal Dimension
IEEE Transactions on Pattern Analysis and Machine Intelligence
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
A Visibility Matching Tone Reproduction Operator for High Dynamic Range Scenes
IEEE Transactions on Visualization and Computer Graphics
Adaptive Split-and-Merge Segmentation Based on Piecewise Least-Square Approximation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple Resolution Texture Analysis and Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image segmentation on a 2D array by a directed split and mergeprocedure
IEEE Transactions on Signal Processing
A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fractal-Based Description of Natural Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gradient watersheds in morphological scale-space
IEEE Transactions on Image Processing
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
Hybrid image segmentation using watersheds and fast region merging
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Speckle reducing anisotropic diffusion
IEEE Transactions on Image Processing
Morphological grayscale reconstruction in image analysis: applications and efficient algorithms
IEEE Transactions on Image Processing
Bayesian learning of generalized gaussian mixture models on biomedical images
ANNPR'10 Proceedings of the 4th IAPR TC3 conference on Artificial Neural Networks in Pattern Recognition
Carotid artery image segmentation using modified spatial fuzzy c-means and ensemble clustering
Computer Methods and Programs in Biomedicine
Journal of Visual Communication and Image Representation
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In many applications of medical image analysis, the density of an object is the most important feature for isolating an area of interest (image segmentation). In this research, an object density-based image segmentation methodology is developed, which incorporates intensity-based, edge-based and texture-based segmentation techniques. The proposed method consists of three main stages: preprocessing, object segmentation and final segmentation. Image enhancement, noise reduction and layer-of-interest extraction are several subtasks of preprocessing. Object segmentation utilizes a marker-controlled watershed technique to identify each object of interest (OI) from the background. A marker estimation method is proposed to minimize over-segmentation resulting from the watershed algorithm. Object segmentation provides an accurate density estimation of OI which is used to guide the subsequent segmentation steps. The final stage converts the distribution of OI into textural energy by using fractal dimension analysis. An energy-driven active contour procedure is designed to delineate the area with desired object density. Experimental results show that the proposed method is 98% accurate in segmenting synthetic images. Segmentation of microscopic images and ultrasound images shows the potential utility of the proposed method in different applications of medical image processing.