Ultrasound Image Enhancement Using An Adaptive Anisotropic Diffusion Filter

Toufique, Yassine; Bouhali, O.

doi:10.5339/qfarc.2014.hbpp0790

Cited by 2 publications

(3 citation statements)

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“…A small change in the gradient value eliminates the noise whereas a large change in the gradient value retains the edges with larger gradient changes. The iterative diffusion filtering is used in anisotropic diffusion filtering [8]. In this study, anisotropic diffusion filter is applied with default gradient threshold and number of iterations.…”

Section: Data Samplementioning

confidence: 99%

“…A unique adaptive anisotropic diffusion filter has been developed without the need for user participation. The developed method automatically calculates the filter parameters based on the noise variance in the image [8]. Techniques namely adaptive histogram equalization and contrast-limited adaptive histogram equalization have been utilised to improve the contrast in ultrasound images [9].…”

Section: Introductionmentioning

confidence: 99%

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Active contour-based segmentation of normal and fetal spina bifida ultrasound images

Ajitha¹,

Punitha²

2022

J. Phys.: Conf. Ser.

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Fetal spina bifida is a neurological disorder which occurs due to improper closure of the spinal column. Fetus identified with spina bifida suffers from various paralytic disorders throughout their lifespan. Early diagnosis of spina bifida aids in timely medical interventions. The ultrasound imaging is widely preferred for fetal monitoring. This study involves segmentation of the normal and abnormal fetal spine from ultrasound images using active contour algorithm. The images for analysis are collected from a diagnostic centre. The noise present in the images is removed using Wiener filter and anisotropic diffusion (AD) filter. The denoised images are evaluated with the metrics such as signal to noise ratio (SNR), peak signal to noise ratio (PSNR), structural similarity index measure (SSIM) and mean square error (MSE). The contrast enhancement is performed by histogram equalization (HE) and adaptive histogram equalization (AHE) techniques. The contrast enhanced images are validated by measures namely entropy and adaptive mean brightness error (AMBE). From the pre-processed image, the spine region is segmented using the active contour method. The results demonstrate that the AD filter with optimal parameters performs better than the Wiener filter for denoising. For the contrast enhancement, the AHE technique shows better performance compared to HE. The active contour technique is able to segment the spine regions in both the normal and spina bifida images. As early diagnosis of spina bifida is essential, this approach could be clinically significant.

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Section: Data Samplementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Active contour-based segmentation of normal and fetal spina bifida ultrasound images

Ajitha¹,

Punitha²

2022

J. Phys.: Conf. Ser.

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“…Ultrasound image processing and analysis find applicatons in several computer aided diagnostic systems [2]. These applications include enhancement of features for better clinical interpretations [3], image filtering for speckle noise reduction methods [4], and segmentation of clinically relevant features such as leisions, tumors, calcification etc. [5] [6].…”

Section: Introductionmentioning

confidence: 99%

Feature Enhancement in Medical Ultrasound Videos Using Multifractal and Contrast Adaptive Histogram Equalization Techniques

Singh

Mukundan

Ryke

2019

2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)

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Speckle noise reduction algorithms are extensively used in the field of ultrasound image analysis with the aim of improving image quality and diagnostic accuracy. However, significant speckle filtering induces blurring, and this would require enhancement of features and fine details. In this paper, we consider the applications of multifractal features and contrast limit adaptive histogram equalization method for improving texture features, contrast, resolvable details, and image structures to which the human visual system is sensitive in ultrasound video frames. The experimental analysis considered various types of ultrasound video scans of the human anatomy e.g. breast cancer, uterine fibroids, transvaginal ovary, ovarian cyst, heart, and chest pleural effusion scan. Subjective assessments by four radiologists and experimental validation using three quality metrics clearly indicate that the proposed algorithm is able to reduce speckle effectively while preserving essential information and enhancing the overall visual quality.

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Ultrasound Image Enhancement Using An Adaptive Anisotropic Diffusion Filter

Cited by 2 publications

References 0 publications

Active contour-based segmentation of normal and fetal spina bifida ultrasound images

Active contour-based segmentation of normal and fetal spina bifida ultrasound images

Feature Enhancement in Medical Ultrasound Videos Using Multifractal and Contrast Adaptive Histogram Equalization Techniques

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