Detail publikace

Segmentation of OPG Images in Studying Jawbone Diseases

Originální název

Segmentation of OPG Images in Studying Jawbone Diseases

Anglický název

Segmentation of OPG Images in Studying Jawbone Diseases

Jazyk

en

Originální abstrakt

Image processing in biomedical applications is strongly developing issue. Many methods and approaches for image preprocessing, segmentation and visualization were described. This paper describes OPG image processing. The aim of processing is to segment regions of jawbone cysts and evaluate their local descriptors. It is necessary to choose suitable segmentation method because of adverse parameters of regions. The regions of the cysts are of low contrast and the pixel intensity distribution is not homogenous. The level set, the watershed and the live-wire segmentation method were chosen to testing. The results are compared. The second step of processing is to evaluate local descriptors of segmented regions which correspond to cysts. Several parameters were chosen to describe these regions – region area, mean gray value of intensities, modal gray value of intensities, standard deviation of intensities, minimal and maximal gray value of intensities, integrated intensity, median of intensities and shape descriptors of region (perimeter, circularity, aspect ratio, roundness and solidity). Values of these parameters will be used in following development of semiautomatic processing method with regard to current assessment of cysts by doctors. The algorithm for classification of the type of cyst is presented.

Anglický abstrakt

Image processing in biomedical applications is strongly developing issue. Many methods and approaches for image preprocessing, segmentation and visualization were described. This paper describes OPG image processing. The aim of processing is to segment regions of jawbone cysts and evaluate their local descriptors. It is necessary to choose suitable segmentation method because of adverse parameters of regions. The regions of the cysts are of low contrast and the pixel intensity distribution is not homogenous. The level set, the watershed and the live-wire segmentation method were chosen to testing. The results are compared. The second step of processing is to evaluate local descriptors of segmented regions which correspond to cysts. Several parameters were chosen to describe these regions – region area, mean gray value of intensities, modal gray value of intensities, standard deviation of intensities, minimal and maximal gray value of intensities, integrated intensity, median of intensities and shape descriptors of region (perimeter, circularity, aspect ratio, roundness and solidity). Values of these parameters will be used in following development of semiautomatic processing method with regard to current assessment of cysts by doctors. The algorithm for classification of the type of cyst is presented.

BibTex


@inproceedings{BUT99300,
  author="Jan {Mikulka}",
  title="Segmentation of OPG Images in Studying Jawbone Diseases",
  annote="Image processing in biomedical applications is strongly developing issue. Many methods and approaches for image preprocessing, segmentation and visualization were described. This paper describes OPG image processing. The aim of processing is to segment regions of jawbone cysts and evaluate their local descriptors. It is necessary to choose suitable segmentation method because of adverse parameters of regions. The regions of the cysts are of low contrast and the pixel intensity distribution is not homogenous. The level set, the watershed and the live-wire segmentation method were chosen to testing. The results are compared. The second step of processing is to evaluate local descriptors of segmented regions which correspond to cysts. Several parameters were chosen to describe these regions – region area, mean gray value of intensities, modal gray value of intensities, standard deviation of intensities, minimal and maximal gray value of intensities, integrated intensity, median of intensities and shape descriptors of region (perimeter, circularity, aspect ratio, roundness and solidity). Values of these parameters will be used in following development of semiautomatic processing method with regard to current assessment of cysts by doctors. The algorithm for classification of the type of cyst is presented.",
  booktitle="Proceedings of PIERS 2013 in Taipei",
  chapter="99300",
  howpublished="online",
  year="2013",
  month="march",
  pages="21--24",
  type="conference paper"
}