Detail publikace

Processing of Magnetic Images of Adipose Tissues

Originální název

Processing of Magnetic Images of Adipose Tissues

Anglický název

Processing of Magnetic Images of Adipose Tissues

Jazyk

en

Originální abstrakt

Sufficiently meaningful picture of tissue structure can be obtained by the correct processing of the image data. This can be done by using image analysis, which takes place in several steps: acquisition of data, image adjustment, segmentation, and image description. At first, digital images are obtained, in our case these are the images of soft tissue obtained with using magnetic resonance tomograph (MR). This device is mainly used to display human tissue in medicine. MR is one of the non-destructive methods, does not cause harmful radiation, whose main advantage is the high contrast in the imaging of soft tissues. The contrast of the resulting images can be changed by setting of the pulse sequence (Spin Echo and Inversion Recovery) timing parameters used to measure the monitored tissue. The data acquired by tomograph is necessary reconstruct by using Fourier Transform reconstruction from K-space in to the MAT file as complex data. The next step of image analysis is image improvement, usually by suppression of noise, histogram equalization and segmentation. Noise should be suppressed to improve results of image processing. Linear transform of histogram was adjusted using a median filter. This is an expansion of the range of brightness in order to cover the entire width of the available brightness. The last step of image processing is multiparametric segmentation. It is a process that divides the image to objects of different characteristic. The main methods include the use of edge detector to highlight certain edges. The last step of the analysis is a description of the image; it is a statistical description of segmented objects in an image with subsequent classification. The aim of this paper is to demonstrate the internal morphology of chicken thigh by using MR. All MR images were evaluated using programs Marevisi and Matlab.

Anglický abstrakt

Sufficiently meaningful picture of tissue structure can be obtained by the correct processing of the image data. This can be done by using image analysis, which takes place in several steps: acquisition of data, image adjustment, segmentation, and image description. At first, digital images are obtained, in our case these are the images of soft tissue obtained with using magnetic resonance tomograph (MR). This device is mainly used to display human tissue in medicine. MR is one of the non-destructive methods, does not cause harmful radiation, whose main advantage is the high contrast in the imaging of soft tissues. The contrast of the resulting images can be changed by setting of the pulse sequence (Spin Echo and Inversion Recovery) timing parameters used to measure the monitored tissue. The data acquired by tomograph is necessary reconstruct by using Fourier Transform reconstruction from K-space in to the MAT file as complex data. The next step of image analysis is image improvement, usually by suppression of noise, histogram equalization and segmentation. Noise should be suppressed to improve results of image processing. Linear transform of histogram was adjusted using a median filter. This is an expansion of the range of brightness in order to cover the entire width of the available brightness. The last step of image processing is multiparametric segmentation. It is a process that divides the image to objects of different characteristic. The main methods include the use of edge detector to highlight certain edges. The last step of the analysis is a description of the image; it is a statistical description of segmented objects in an image with subsequent classification. The aim of this paper is to demonstrate the internal morphology of chicken thigh by using MR. All MR images were evaluated using programs Marevisi and Matlab.

BibTex


@inproceedings{BUT99237,
  author="Michaela {Pokludová} and Eva {Gescheidtová} and Jan {Mikulka}",
  title="Processing of Magnetic Images of Adipose Tissues",
  annote="Sufficiently meaningful picture of tissue structure can be obtained by the correct processing of the image data. This can be done by using image analysis, which takes place in several steps: acquisition of data, image adjustment, segmentation, and image description. At first, digital images are obtained, in our case these are the images of soft tissue obtained with using magnetic resonance tomograph (MR). This device is mainly used to display human tissue in medicine. MR is one of the non-destructive methods, does not cause harmful radiation, whose main advantage is the high contrast in the imaging of soft tissues. The contrast of the resulting images can be changed by setting of the pulse sequence (Spin Echo and Inversion Recovery) timing parameters used to measure the monitored tissue. The data acquired by tomograph is necessary reconstruct by using Fourier Transform reconstruction from K-space in to the MAT file as complex data. The next step of image analysis is image improvement, usually by suppression of noise, histogram equalization and segmentation. Noise should be suppressed to improve results of image processing. Linear transform of histogram was adjusted using a median filter. This is an expansion of the range of brightness in order to cover the entire width of the available brightness. The last step of image processing is multiparametric segmentation. It is a process that divides the image to objects of different characteristic. The main methods include the use of edge detector to highlight certain edges. The last step of the analysis is a description of the image; it is a statistical description of segmented objects in an image with subsequent classification. The aim of this paper is to demonstrate the internal morphology of chicken thigh by using MR. All MR images were evaluated using programs Marevisi and Matlab.",
  address="The Electromagnetic Academy, USA",
  booktitle="PIERS PROCEEDINGS Progress In Electromagnetics Research Symposium",
  chapter="99237",
  howpublished="online",
  institution="The Electromagnetic Academy, USA",
  year="2013",
  month="march",
  pages="385--387",
  publisher="The Electromagnetic Academy, USA",
  type="conference paper"
}