Ultrasound Fetal Image Segmentation Techniques: A Review

2018 ◽  
Vol 15 (1) ◽  
pp. 52-60
Author(s):  
S. Jayanthi Sree ◽  
C. Vasanthanayaki
Keyword(s):  
Image Segmentation ◽  
Image Quality ◽  
Gestational Age ◽  
Ultrasound Images ◽  
Fetal Ultrasound ◽  
Segmentation Algorithms ◽  
Biological Structures ◽  
2D Ultrasound

Background: This paper reviews segmentation techniques for 2D ultrasound fetal images. Fetal anatomy measurements derived from the segmentation results are used to monitor the growth of the fetus. </P><P> Discussion: The segmentation of fetal ultrasound images is a difficult task due to inherent artifacts and degradation of image quality with gestational age. There are segmentation techniques for particular biological structures such as head, stomach, and femur. The whole fetal segmentation algorithms are only very few. Conclusion: This paper presents a review of these segmentation techniques and the metrics used to evaluate them are summarized.

scholarly journals Motion blur invariant for estimating motion parameters of medical ultrasound images

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Barmak Honarvar Shakibaei Asli ◽  
Yifan Zhao ◽  
John Ahmet Erkoyuncu
Keyword(s):  
Image Quality Assessment ◽  
Medical Image Analysis ◽  
Main Idea ◽  
Delta Function ◽  
Motion Blur ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Fetal Ultrasound ◽  
Dirac Delta ◽  
Motion Parameters

AbstractHigh-quality medical ultrasound imaging is definitely concerning motion blur, while medical image analysis requires motionless and accurate data acquired by sonographers. The main idea of this paper is to establish some motion blur invariant in both frequency and moment domain to estimate the motion parameters of ultrasound images. We propose a discrete model of point spread function of motion blur convolution based on the Dirac delta function to simplify the analysis of motion invariant in frequency and moment domain. This model paves the way for estimating the motion angle and length in terms of the proposed invariant features. In this research, the performance of the proposed schemes is compared with other state-of-the-art existing methods of image deblurring. The experimental study performs using fetal phantom images and clinical fetal ultrasound images as well as breast scans. Moreover, to validate the accuracy of the proposed experimental framework, we apply two image quality assessment methods as no-reference and full-reference to show the robustness of the proposed algorithms compared to the well-known approaches.

Postnatal ultrasound follow-up in neonates with prenatal hydronephrosis

Diagnosis ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Elham Kebriyaei ◽  
Ali Davoodi ◽  
Seyed Alinaghi Kazemi ◽  
Zahra Bazargani
Keyword(s):  
Ultrasound Imaging ◽  
Maternal Education ◽  
Left Kidney ◽  
Ultrasound Images ◽  
Fetal Ultrasound ◽  
Renal Anomalies ◽  
Cross Sectional ◽  
Fetal Hydronephrosis ◽  
Kidney Involvement

Abstract Objectives Renal anomalies are the most common fetal abnormalities that occur during prenatal development, and are typically detected by observing hydronephrosis on fetal ultrasound imaging. Follow-up with post-natal ultrasound is important to detect clinically-important obstruction, because many of the pre-natal abnormalities resolve spontaneously. This study aimed to evaluate the postnatal hydronephrosis follow-up rate, and reasons for non follow-up in affected neonates. Methods In this cross-sectional study all neonates born during a period of one year at Ayatollah Mousavi Hospital with hydronephrosis on fetal ultrasound imaging were recruited. All mothers were also given face-to-face information about fetal hydronephrosis and its postnatal outcomes, and follow-up with at least a postnatal ultrasound was recommended from the fourth day of their neonates’ birth until the end of the fourth week. The neonates were subsequently observed for one month to determine the postnatal ultrasound follow-up rate and to reflect on diagnostic test results, reasons for failure to follow-up, as well as causes of hydronephrosis. Results In this study, 71 cases (1.2%) out of 5,952 neonates had fetal hydronephrosis on prenatal ultrasound images. The postnatal ultrasound imaging showed kidney involvement in 18 neonates (25%), particularly in the left kidney (61.1%). Seven neonates had no follow-up at one month (10%). No significant relationship was found between lack of follow-up and the neonates’ place of residence (p=0.42), maternal education (p=0.90), number of siblings (p=0.33), or gender (p=0.64). Conclusions Postnatal ultrasound follow-up rate in these neonates with a history of fetal hydronephrosis was incomplete even though parents had been provided with education and advice at their birth time. Accordingly, it is recommended to perform postnatal ultrasound once neonates are discharged from hospitals.

scholarly journals A NOVEL IMAGE SEGMENTATION APPROACH BASED ON NEUTROSOPHIC SET AND IMPROVED FUZZY C-MEANS ALGORITHM

2011 ◽  
Vol 07 (01) ◽  
pp. 155-171 ◽  
Author(s):  
H. D. CHENG ◽  
YANHUI GUO ◽  
YINGTAO ZHANG
Keyword(s):  
Image Segmentation ◽  
Point Of View ◽  
Neutrosophic Set ◽  
Convergence Criterion ◽  
Complex Objects ◽  
Fuzzy C Means ◽  
Segmentation Methods ◽  
Segmentation Algorithms ◽  
Segmentation Approach ◽  
Fuzzy C Means Algorithm

Image segmentation is an important component in image processing, pattern recognition and computer vision. Many segmentation algorithms have been proposed. However, segmentation methods for both noisy and noise-free images have not been studied in much detail. Neutrosophic set (NS), a part of neutrosophy theory, studies the origin, nature, and scope of neutralities, as well as their interaction with different ideational spectra. However, neutrosophic set needs to be specified and clarified from a technical point of view for a given application or field to demonstrate its usefulness. In this paper, we apply neutrosophic set and define some operations. Neutrosphic set is integrated with an improved fuzzy c-means method and employed for image segmentation. A new operation, α-mean operation, is proposed to reduce the set indeterminacy. An improved fuzzy c-means (IFCM) is proposed based on neutrosophic set. The computation of membership and the convergence criterion of clustering are redefined accordingly. We have conducted experiments on a variety of images. The experimental results demonstrate that the proposed approach can segment images accurately and effectively. Especially, it can segment the clean images and the images having different gray levels and complex objects, which is the most difficult task for image segmentation.

Cell-Based Two-Region Competition Algorithm with a Map Framework for Boundary Delineation of a Series of 2D Ultrasound Images

2007 ◽  
Vol 33 (10) ◽  
pp. 1640-1650 ◽  
Author(s):  
Jie-Zhi Cheng ◽  
Chung-Ming Chen ◽  
Yi-Hong Chou ◽  
Curtis S.K. Chen ◽  
Chui-Mei Tiu ◽  
...  
Keyword(s):  
Ultrasound Images ◽  
2D Ultrasound
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