Localizing Region-Based Level-set Contouring for Common Carotid Artery in Ultrasonography

Chen, Yong; Zhou, Xiao Yi; Dong, Cheng-Di

doi:10.12928/telkomnika.v11i4.1202

Cited by 2 publications

(1 citation statement)

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“…Compared to other modalities such as CT scans and MRI, the ultrasound has the lower price, easy to move (portable), small and easily manipulated, and non -ionizing [1], [2]. Besides being used to monitor pregnancy, the ultrasonography is widely used for examination of diseases such as liver cancer [3], cardiovascular disease [4], breast cancer [5], [6], and musculoskeletal disorders [7]. Nevertheless, there are many drawbacks of this modality such as the artefacts on ultrasound images that named speckle noise.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Speckle Noise Reduction Method for Abdominal Circumference Segmentation of Fetal Ultrasound Images

Hermawati

Tjandrasa

Suciati

2018

IJECE

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Fetal biometric size such as abdominal circumference (AC) is used to predict fetal weight or gestational age in ultrasound images. The automatic biometric measurement can improve efficiency in the ultrasonography examination workflow. The unclear boundaries of the abdomen image and the speckle noise presence are the challenges for the automated AC measurement techniques. The main problem to improve the accuracy of the automatic AC segmentation is how to remove noise while retaining the boundary features of objects. In this paper, we proposed a hybrid ultrasound image denoising framework which was a combination of spatial-based filtering method and multiresolution based method. In this technique, an ultrasound image was decomposed into subbands using wavelet transform. A thresholding technique and the anisotropic diffusion method were applied to the detail subbands, at the same time the bilateral filtering modified the approximation subband. The proposed denoising approach had the best performance in the edge preservation level and could improve the accuracy of the abdominal circumference segmentation.

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