Segmentation of spinal cord images by means of watershed and region merging together with inhomogeneity correction

• Autorzy: Nieniewski M. , Serneels R.
• Języki publikacji: EN

Abstrakty

EN

The paper presents a morphological method for segmentation of high field Mahnetic Resonance (MR) images of the human spinal cord and extraction of the gray matter mask. These images are of low quality and poor contrast. The inhomogeneity of brightness in thr image is usully more pronounced than the difference in brightness between the gray matter and the white matter. Due to this inhomogeneity, it is very hard to use watershed segmentation for automatic extraction of the gray matter, and what remains is manual pointing out of a hundred or more regions belonging to the gray matter. However, as shown in the paper, by using the White Top Hat (WHT) transform with a large structuring element, one can correct the images, significantly reducing the inhomogeneity and approprioriginal image, whereas region statistics used for region merging are calculated from the corrected image. Then the extraction of the gray matter mask is carried out in a semi-automatic way, with the user pointing out the first region belonging to the gray matter area, and the program selecting subsequent neighboring regions based on the statistics of the regions. The method was tested on images coming from different cross-sections of the spinal cord, and the results indicate that the process of extracing the gray matter mask has been significantly speeded up and improved.

Słowa kluczowe

EN

spinal cord; extraction of gray matter; correlation of MR images; watershed; region merging

• Wydawca: Institute of Information Technology of the Warsaw University of Life Sciences – SGGW
• Czasopismo: Machine Graphics and Vision
• Rocznik: 2002
• Tom: Vol. 11, No. 1
• Strony: 101--121
• Opis fizyczny: Bibliogr. 20 poz.

Twórcy

autor

Nieniewski M.

• Institute of Fundamental Technological Research, Warsaw, Poland
• Electrotechnical Institute, Warsaw, Poland

autor

Serneels R.

• Limburg University Center, Diepenbeek, Belgium

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