Carotid wall segmentation in longitudinal ultrasound images using structured random forest
| Autor: | A. V. Narasimhadhan, A Hema Sai Teja, C S Asha, Y Nagaraj |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
General Computer Science
business.industry Computer science Speckle noise Pattern recognition Image processing 02 engineering and technology Image segmentation Object detection Edge detection 030218 nuclear medicine & medical imaging Random forest 03 medical and health sciences 0302 clinical medicine Control and Systems Engineering Region of interest 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Segmentation Artificial intelligence Electrical and Electronic Engineering business |
| Zdroj: | Computers & Electrical Engineering. 69:753-767 |
| ISSN: | 0045-7906 |
| DOI: | 10.1016/j.compeleceng.2018.02.010 |
| Popis: | Edge detection is a primary image processing technique used for object detection, data extraction, and image segmentation. Recently, edge-based segmentation using structured classifiers has been receiving increasing attention. The intima media thickness (IMT) of the common carotid artery is mainly used as a primitive indicator for the development of cardiovascular disease. For efficient measurement of the IMT, we propose a fast edge-detection technique based on a structured random forest classifier. The accuracy of IMT measurement is degraded owing to the speckle noise found in carotid ultrasound images. To address this issue, we propose the use of a state-of-the-art denoising method to reduce the speckle noise, followed by an enhancement technique to increase the contrast. Furthermore, we present a novel approach for an automatic region of interest extraction in which a pre-trained structured random forest classifier algorithm is applied for quantifying the IMT. The proposed method exhibits IMTmean ± standard deviation of 0.66mm ± 0.14, which is closer to the ground truth value 0.67mm ± 0.15 as compared to the state-of-the-art techniques. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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