PMID- 26441443
OWN - NLM
STAT- MEDLINE
DCOM- 20170713
LR  - 20171109
IS  - 1558-2531 (Electronic)
IS  - 0018-9294 (Linking)
VI  - 63
IP  - 6
DP  - 2016 Jun
TI  - A New Feature-Enhanced Speckle Reduction Method Based on Multiscale Analysis for 
      Ultrasound B-Mode Imaging.
PG  - 1178-91
LID - 10.1109/TBME.2015.2486042 [doi]
AB  - Effective speckle reduction in ultrasound B-mode imaging is important for 
      enhancing the image quality and improving the accuracy in image analysis and 
      interpretation. In this paper, a new feature-enhanced speckle reduction (FESR) 
      method based on multiscale analysis and feature enhancement filtering is proposed 
      for ultrasound B-mode imaging. In FESR, clinical features (e.g., boundaries and 
      borders of lesions) are selectively emphasized by edge, coherence, and contrast 
      enhancement filtering from fine to coarse scales while simultaneously suppressing 
      speckle development via robust diffusion filtering. In the simulation study, the 
      proposed FESR method showed statistically significant improvements in edge 
      preservation, mean structure similarity, speckle signal-to-noise ratio, and 
      contrast-to-noise ratio (CNR) compared with other speckle reduction methods, 
      e.g., oriented speckle reducing anisotropic diffusion (OSRAD), nonlinear 
      multiscale wavelet diffusion (NMWD), the Laplacian pyramid-based nonlinear 
      diffusion and shock filter (LPNDSF), and the Bayesian nonlocal means filter 
      (OBNLM). Similarly, the FESR method outperformed the OSRAD, NMWD, LPNDSF, and 
      OBNLM methods in terms of CNR, i.e., 10.70 +/- 0.06 versus 9.00 +/- 0.06, 9.78 +/- 
      0.06, 8.67 +/- 0.04, and 9.22 +/- 0.06 in the phantom study, respectively. 
      Reconstructed B-mode images that were developed using the five speckle reduction 
      methods were reviewed by three radiologists for evaluation based on each 
      radiologist's diagnostic preferences. All three radiologists showed a significant 
      preference for the abdominal liver images obtained using the FESR methods in 
      terms of conspicuity, margin sharpness, artificiality, and contrast, p<0.0001. 
      For the kidney and thyroid images, the FESR method showed similar improvement 
      over other methods. However, the FESR method did not show statistically 
      significant improvement compared with the OBNLM method in margin sharpness for 
      the kidney and thyroid images. These results demonstrate that the proposed FESR 
      method can improve the image quality of ultrasound B-mode imaging by enhancing 
      the visualization of lesion features while effectively suppressing speckle noise.
FAU - Kang, Jinbum
AU  - Kang J
FAU - Lee, Jae Young
AU  - Lee JY
FAU - Yoo, Yangmo
AU  - Yoo Y
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20151002
PL  - United States
TA  - IEEE Trans Biomed Eng
JT  - IEEE transactions on bio-medical engineering
JID - 0012737
SB  - IM
MH  - Algorithms
MH  - Humans
MH  - Image Interpretation, Computer-Assisted/*methods
MH  - Kidney/diagnostic imaging
MH  - Phantoms, Imaging
MH  - Signal-To-Noise Ratio
MH  - Thyroid Gland/diagnostic imaging
MH  - Ultrasonography/*methods
EDAT- 2015/10/07 06:00
MHDA- 2017/07/14 06:00
CRDT- 2015/10/07 06:00
PHST- 2015/10/07 06:00 [entrez]
PHST- 2015/10/07 06:00 [pubmed]
PHST- 2017/07/14 06:00 [medline]
AID - 10.1109/TBME.2015.2486042 [doi]
PST - ppublish
SO  - IEEE Trans Biomed Eng. 2016 Jun;63(6):1178-91. doi: 10.1109/TBME.2015.2486042. 
      Epub 2015 Oct 2.