Image segmentation and feature extraction

Atam P. Dhawan

doi:10.1142/9789812814807_0009

Image segmentation and feature extraction

Atam P. Dhawan

Research output: Chapter in Book/Report/Conference proceeding › Chapter

3 Scopus citations

Abstract

Medical image segmentation tasks are important to visualize features of interests such as lesions with boundary and volume information. Similar information is required in the computerized quantitative analysis and classification for diagnostic evaluation and characterization. This chapter presents some of the most effective and commonly used edge and region segmentation methods. Statistical quantitative features from gray level distribution, segmented regions, and texture in the image are also presented.

Original language	English (US)
Title of host publication	Principles and Advanced Methods in Medical Imaging and Image Analysis
Publisher	World Scientific Publishing Co.
Pages	197-228
Number of pages	32
ISBN (Electronic)	9789812814807
ISBN (Print)	9789812705341
DOIs	https://doi.org/10.1142/9789812814807_0009
State	Published - Jan 1 2008

All Science Journal Classification (ASJC) codes

General Medicine

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10.1142/9789812814807_0009

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title = "Image segmentation and feature extraction",

abstract = "Medical image segmentation tasks are important to visualize features of interests such as lesions with boundary and volume information. Similar information is required in the computerized quantitative analysis and classification for diagnostic evaluation and characterization. This chapter presents some of the most effective and commonly used edge and region segmentation methods. Statistical quantitative features from gray level distribution, segmented regions, and texture in the image are also presented.",

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AB - Medical image segmentation tasks are important to visualize features of interests such as lesions with boundary and volume information. Similar information is required in the computerized quantitative analysis and classification for diagnostic evaluation and characterization. This chapter presents some of the most effective and commonly used edge and region segmentation methods. Statistical quantitative features from gray level distribution, segmented regions, and texture in the image are also presented.

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M3 - Chapter

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BT - Principles and Advanced Methods in Medical Imaging and Image Analysis

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ER -

Image segmentation and feature extraction

Abstract

All Science Journal Classification (ASJC) codes

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