Segmentation and Boundary Detection of Fetal Kidney Images in Second and Third Trimesters Using Kernel-Based Fuzzy Clustering.

Organ segmentation is an important step in Ultrasound fetal images for early prediction of congenital abnormalities and to estimate delivery date. In many applications of 2D medical imaging, they face problems with speckle noise and object contours. Frequent scanning of fetal leads to clinical distu...

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Publicado en:Journal of Medical Systems Vol. 43; no. 7
Autores principales: Meenakshi, S., Suganthi, M., Sureshkumar, P.
Formato: computer program diagnostic images equations & formulas tables/charts Journal Article
Publicado: Springer Nature Jul2019
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jul2019
      vid: 43
      iid: 7
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10916-019-1324-3
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        atl: Segmentation and Boundary Detection of Fetal Kidney Images in Second and Third Trimesters Using Kernel-Based Fuzzy Clustering.
      aug:
        au:
          Meenakshi, S.
          Suganthi, M.
          Sureshkumar, P.
        affil: Mahendra College of Engineering, 636106, Salem, India
      sug:
        subj:
          Ultrasonography, Prenatal
          Signal Processing, Computer Assisted
          Kidney Ultrasonography
          Algorithms
          Abnormalities Prevention and Control
          Artifacts
          Validity
          Image Enhancement Methods
          Image Interpretation, Computer Assisted
          Noise
          Fetus
          Pregnancy Trimester, Second
          Pregnancy
          Female
          Pregnancy Trimester, Third
          Fetus, conception to birth
          Female
      ab: Organ segmentation is an important step in Ultrasound fetal images for early prediction of congenital abnormalities and to estimate delivery date. In many applications of 2D medical imaging, they face problems with speckle noise and object contours. Frequent scanning of fetal leads to clinical disturbances to the fetal growth and the quantitative interpretation of Ultrasonic images also a difficult task compared to other image modalities. In the present work a three-stage hybrid algorithm has been developed to segment the US fetal kidney images for the detection of shape and contour. At the first stage the hybrid Mean Median (Hybrid MM) filter is applied to reduce the speckle noise. Then a kernel based Fuzzy C - means clustering is used to detect the shape and contour. Finally, the texture features are obtained from the segmented images. Based on the obtained texture features, the abnormalities are detected. The Gaussian Radial basis function provides an accuracy of 80% at the second and third trimesters with weighted constant ranging from 4 to 8, compared to other global kernel functions. Similarly the proposed method has an accuracy of 86% with compared to other FCM techniques.
      pubtype: Academic Journal
      doctype:
        computer program
        diagnostic images
        equations & formulas
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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