Key result
Adaptive wind-driven optimization improves automatic intima-media complex segmentation over state-of-the-art methods.
The proposed adaptive wind driven optimization technique provides an improved automated method for segmenting the intima media complex in carotid ultrasound images.
May support automated CIMT research; leaves open prospective clinical validation before practice change.
Cardiovascular diseases have been one of the leading causes of death and have been increasing in much of the developing world. Atherosclerosis, the accumulation of plaque on artery walls is the major for cardiovascular diseases. This is diagnosed by measuring the thickness of IMC of common carotid artery (CCA) in ultrasound images. In this paper, we present a completely automatic technique for segmentation of IMC in ultrasound images of CCA. The image is segmented using adaptive wind driven optimization (AWDO) technique. The denoising filter based on Bayesian least square approach and a robust enhancement technique is used in the pre-processing stage. The proposed method is evaluated on 60 ultrasound images and is compared with the state-of-the-art methods. The experimental results show that the proposed method yields better results as compared to other methods.
No takes yet. Share an insight, caveat, or question.
Madipalli et al. (2018) studied Atherosclerosis (n=60). Adaptive wind driven optimization (AWDO) technique vs. State-of-the-art methods was evaluated on Segmentation of intima media complex (IMC). An automatic segmentation technique using adaptive wind driven optimization yielded better results for segmenting the intima media complex in 60 ultrasound images compared to state-of-the-art methods.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: