Despeckling with Structure Preservation in Clinical Ultrasound Images Using Historical Edge Information Weighted Regularizer

  • Rahul Roy
  • Susmita Ghosh
  • Sung-Bae Cho
  • Ashish Ghosh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10682)


This article presents a de-speckling technique for clinical ultrasound images with an aim to preserve the fine structural information and region boundaries in images. The algorithm generates restored images by minimizing the variational energy on them. To compute variational energy, a weighted total variation based method is proposed where the weights are determined from both historical (previous/earlier time stamp) as well as instantaneous oriented structural information of images. This helps in defining the anistropy at edges in the image which, in turn, helps in identifying homogenous regions on it. Moreover, the method is able to preserve the vague echo-textural differences which might be of clinical importance but may get destroyed due to smoothing operations. To elicit effectiveness, comparative analysis of the proposed approaches have been done with four state-of-the-art techniques on both in silico and in vivo ultrasound images using four standard measures (two for phantom images and two for clinical ultrasound images). Qualitative and quantitative analysis reveals the promising performance of the proposed technique.


Clinical ultrasound image Speckle de-noising Bayesian MAP Bregman alternate method of multipliers 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Rahul Roy
    • 1
  • Susmita Ghosh
    • 2
  • Sung-Bae Cho
    • 3
  • Ashish Ghosh
    • 1
  1. 1.Machine Intelligence UnitIndian Statistical InstituteKolkataIndia
  2. 2.Department of Computer Science and EngineeringJadavpur UniversityKolkataIndia
  3. 3.Soft Computing Laboratory, Department of Computer ScienceYonsei UniversitySeoulKorea

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