title: A fast 3D adaptive bilateral filter for ultrasound volume visualization.
abstract: OBJECTIVE
  This paper introduces an effective noise removal method for medical ultrasound volume data. Ultrasound data usually need to be filtered because they contain significant noise. Conventional two-dimensional (2D) filtering methods cannot use the implicit information between adjacent layers, and existing 3D filtering methods are slow because of complicated filter kernels. Even though one filter method utilizes simple filters for speed, it is inefficient at removing noise and does not take into account the characteristics of ultrasound sampling. To solve this problem, we introduce a fast filtering method using parallel bilateral filtering and adjust the filter window size proportionally according to its position.
  
  
  METHODS
  We devised a parallel bilateral filtering by obtaining a 3D summed area table of a quantized spatial filter. The filtering method is made adaptive by changing the kernel window size according to the distance from the ultrasound signal transmission point.
  
  
  RESULTS
  Experiments were performed to compare the noise removal and loss of original data of the anisotropic diffusion filtering, bilateral filtering, and adaptive bilateral filtering of ultrasound volume-rendered images. The results show that the adaptive filter correctly takes into account the sampling characteristics of the ultrasound volumes.
  
  
  CONCLUSIONS
  The proposed method can more efficiently remove noise and minimize distortion from ultrasound data than existing simple or non-adaptive filtering methods.
authors.affiliation: Department of Computer Science and Information Engineering, Inha University, Incheon, Republic of Korea.
authors.forename: Koojoo
authors.initials: K
authors.lastname: Kwon
authors.affiliation: Department of Computer Science and Information Engineering, Inha University, Incheon, Republic of Korea.
authors.forename: Min-Su
authors.initials: MS
authors.lastname: Kim
authors.affiliation: Department of Computer Science and Information Engineering, Inha University, Incheon, Republic of Korea. Electronic address: bsshin@inha.ac.kr.
authors.forename: Byeong-Seok
authors.initials: BS
authors.lastname: Shin
mesh_terms: D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D011247:Pregnancy; D016216:Ultrasonography, Prenatal
keywords: Adaptive filtering; Bilateral filtering; Ultrasound data filtering; Ultrasound volume data