Spatially constrained distance regularized level set evolution method for segmentation of hydrops fetalis from ultrasound fetal heart images

Nageswari, C. Shobana; Prabha, K.

doi:10.1007/s10617-017-9199-3

Cited by 3 publications

(1 citation statement)

References 19 publications

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“…The above method does not have a parallel processing capability, so it has a high computational load. Nagesvari 9 proposed a spatial limitation on DRLSE, which has improved the contrast and quality of the processed image and reduced the computational load. The main problem of this method is the need for human intervention in the analysis process.…”

Section: Introductionmentioning

confidence: 99%

Local energy-based image region segmentation using Legendre polynomials

Mahmoudian

Niazi

2023

J. Electron. Imag.

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.Segmentation of images is a critical pre-processing step in image processing. The objective of segmentation is to divide an image into two homogeneous segments based on similar features. Recently, energy-based segmentation methods, such as the level set algorithm, have exhibited remarkable performance in segmenting various types of image data. However, such methods fail to produce satisfactory results on textured images, leading to inaccurate foreground and background segmentation. To address this issue, the proposed method utilizes a feature space based on image local energy, which is independent of image intensity. This feature space provides a more robust representation of texture in the image. By taking advantage of a unique feature space, images can be represented with a sum of Legendre polynomials. The reproduced image is injected into the L2S algorithm. The level set function is optimized from the average difference of Legendre polynomial coefficients to provide the best representation of the image. Consequently, the proposed method results in better segmentation accuracy, with an average increase of 19.33 compared to existing state-of-the-art methods.

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Section: Introductionmentioning

confidence: 99%

Local energy-based image region segmentation using Legendre polynomials

Mahmoudian

Niazi

2023

J. Electron. Imag.

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Review of Level Set in Image Segmentation

Wang

Zhu

2020

Arch Computat Methods Eng

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The Classification and Segmentation of Fetal Anatomies Ultrasound Image: A Survey

Song

Gao

Hong

et al. 2021

j med imaging hlth inform

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Ultrasound imaging processing technology has been used in obstetric observation of the fetus and diagnosis of fetal diseases for more than half a century. It contains certain advantages and unique challenges which has been developed rapidly. From the perspective of ultrasound image analysis, at the very beginning, it is essential to determine fetal survival, gestational age and so on. Currently, the fetal anatomies ultrasound image analysis approaches have been studies and it has become an indispensable diagnostic tool for diagnosing fetal abnormalities, in order to gain more insight into the ongoing development of the fetus. Presently, it is the time to review previous approaches systematically in this field and to predict the directions of the future. Thus, this article reviews state-of-art approaches with the basic ideas, theories, pros and cons of ultrasound image technique for whole fetus with other anatomies. First of all, it summarizes the current pending problems and introduces the popular image processing methods, such as classification, segmentation etc. After that, the advantages and disadvantages in existing approaches as well as new research ideas are briefly discussed. Finally, the challenges and future trend are discussed.

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Spatially constrained distance regularized level set evolution method for segmentation of hydrops fetalis from ultrasound fetal heart images

Cited by 3 publications

References 19 publications

Local energy-based image region segmentation using Legendre polynomials

Local energy-based image region segmentation using Legendre polynomials

Review of Level Set in Image Segmentation

The Classification and Segmentation of Fetal Anatomies Ultrasound Image: A Survey

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