An Enhanced Method for Automatic Detection and Segmentation of Carotid Artery in Ultrasound Images

Ličev, Lačezar; Feberova, Karolina; Tomecek, Jan; Hendrych, Jakub

doi:10.1145/2983468.2983483

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…One research that utilized ultrasonic imaging to process carotid artery transactions was conducted by Licev et al [19]. For artery identification, they employed the Hough transform.…”

Section: Related Workmentioning

confidence: 99%

Automatic Segmentation and Detection System for Varicocele Using Ultrasound Images

Abdalla¹,

Awad²,

AlZoubi³

et al. 2022

Computers, Materials &Amp; Continua

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The enlarged veins in the pampiniform venous plexus, known as varicocele disease, are typically identified using ultrasound scans. The medical diagnosis of varicocele is based on examinations made in three positions taken to the right and left testicles of the male patient. The proposed system is designed to determine whether a patient is affected. Varicocele is more frequent on the left side of the scrotum than on the right and physicians commonly depend on the supine position more than other positions. Therefore, the experimental results of this study focused on images taken in the supine position of the left testicles of patients. There are two possible vein structures in each image: a cross-section (circular) and a tube (non-circular) structure. This proposed system identifies dilated (varicocele) veins of these structures in ultrasound images in three stages: preprocessing, processing, and detection and measurement. These three stages are applied in three different color modes: Grayscale, Red-Green-Blue (RGB), and Hue, Saturation, and Value (HSV). In the preprocessing stage, the region of interest enclosing the pampiniform plexus area is extracted using a median filter and threshold segmentation. Then, the processing stage employs different filters to perform image denoising. Finally, edge detection is applied in multiple steps and the detected veins are measured to determine if dilated veins exist. Overall implementation results showed the proposed system is faster and more effective than the previous work.

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“…One research that utilized ultrasonic imaging to process carotid artery transactions was conducted by Licev et al [19]. For artery identification, they employed the Hough transform.…”

Section: Related Workmentioning

confidence: 99%

Automatic Segmentation and Detection System for Varicocele Using Ultrasound Images

Abdalla¹,

Awad²,

AlZoubi³

et al. 2022

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…A method for processing carotid arteries using ultrasonic images was proposed by [19]. They used the Hough transform (HT) for artery detection.…”

Section: Related Workmentioning

confidence: 99%

Automatic Segmentation and Detection System for Varicocele in Supine Position

2021

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Image analysis is an important technique that can help specialists localize, detect and segment objects in different types of medical images such as MRI, CTs, and Ultrasounds (US). In this research, we use US images to identify and segment the enlarged veins in the pampiniform venous plexus, which is called varicocele. The proposed method aims to determine whether a potential patient is affected or not. This method was evaluated on 90 US images that were taken to the left testicles of 90 patients using the Supine position. This system analyzes US images in three stages which are; preprocessing, processing, and edge detection. The Region Of Interest (ROI) of the pampiniform plexus area was extracted using Otsu segmentation with different parameters 0.1, 0.2, and 0.17, and different color modes (Grayscale, YCbCr, RGB). In the processing stage, different denoising filters were used. Eventually, in the edge detection stage, four edge detectors were applied which are Canny, Soble, Prewitt, and Roberts. Results showed that the best accuracy in detecting varicocele was 78% when YCbCr color mode yellow (y) channel is used with 0.1 Otsu segmentation and the Canny edge detector. The system also showed a Sensitivity of 91%, the test was able to detect 91% of the people with Varicocele, and a Specificity of 39%.

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An Enhanced Method for Automatic Detection and Segmentation of Carotid Artery in Ultrasound Images

Cited by 2 publications

References 14 publications

Automatic Segmentation and Detection System for Varicocele Using Ultrasound Images

Automatic Segmentation and Detection System for Varicocele Using Ultrasound Images

Automatic Segmentation and Detection System for Varicocele in Supine Position

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