Detail publikace

Pre-Processing Computer Tomography Images for Segmentation Based on Region Growing Methods

Originální název

Pre-Processing Computer Tomography Images for Segmentation Based on Region Growing Methods

Anglický název

Pre-Processing Computer Tomography Images for Segmentation Based on Region Growing Methods

Jazyk

en

Originální abstrakt

This paper introduces an image pre-processing technique for the augmentation of segmentation of medical images. The proposed pre-processing method down-samples an image histogram for spreading important features to same intensity in CT image. However, some information is lost in this process. Therefore Bayes approach was applied to improve resulted inaccuracies. The method brings significant advantages for the image analysis: 1. the regions of interests are subjectively more visible, 2. the resulted image is represented by less gray scales which makes the following segmentation easier.

Anglický abstrakt

This paper introduces an image pre-processing technique for the augmentation of segmentation of medical images. The proposed pre-processing method down-samples an image histogram for spreading important features to same intensity in CT image. However, some information is lost in this process. Therefore Bayes approach was applied to improve resulted inaccuracies. The method brings significant advantages for the image analysis: 1. the regions of interests are subjectively more visible, 2. the resulted image is represented by less gray scales which makes the following segmentation easier.

BibTex


@inproceedings{BUT14904,
  author="Tomáš {Červinka} and Ivo {Provazník}",
  title="Pre-Processing Computer Tomography Images for Segmentation Based on Region Growing Methods",
  annote="This paper introduces an image pre-processing technique for the augmentation of segmentation of medical images. The proposed pre-processing method down-samples an image histogram for spreading important features to same intensity in CT image. However, some information is lost in this process. Therefore Bayes approach was applied to improve resulted inaccuracies. The method brings significant advantages for the image analysis: 1. the regions of interests are subjectively more visible, 2. the resulted image is represented by less gray scales which makes the following segmentation easier.",
  address="IFBME",
  booktitle="Proceedings of 3rd International Conference EMBEC 2005",
  chapter="14904",
  institution="IFBME",
  year="2005",
  month="november",
  pages="1",
  publisher="IFBME",
  type="conference paper"
}