Improvement of Lesion Detectability by Speckle Reduction Filtering: A Quantitative Study

Verhoeven, Jonas

doi:10.1006/uimg.1993.1012

Cited by 27 publications

(7 citation statements)

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“…In these studies [4,18], speckle reduction filtering was evaluated based only on visual perception evaluation made by the researchers. Verhoeven et al [29] applied mean and median filtering in simulated ultrasound images and in ultrasound images with blood vessels. The lesion-signal-to-noise ratio was used in order to quantify the detectability of lesions after filtering.…”

Section: Discussionmentioning

confidence: 99%

Quality evaluation of ultrasound imaging in the carotid artery based on normalization and speckle reduction filtering

et al. 2006

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Image quality is important when evaluating ultrasound images of the carotid for the assessment of the degree of atherosclerotic disease, or when transferring images through a telemedicine channel, and/or in other image processing tasks. The objective of this study was to investigate the usefulness of image quality evaluation based on image quality metrics and visual perception, in ultrasound imaging of the carotid artery after normalization and speckle reduction filtering. Image quality was evaluated based on statistical and texture features, image quality evaluation metrics, and visual perception evaluation made by two experts. These were computed on 80 longitudinal ultrasound images of the carotid bifurcation recorded from two different ultrasound scanners, the HDI ATL-3000 and the HDI ATL-5000 scanner, before (NF) and after (DS) speckle reduction filtering, after normalization (N), and after normalization and speckle reduction filtering (NDS). The results of this study showed that: (1) the normalized speckle reduction, NDS, images were rated visually better on both scanners; (2) the NDS images showed better statistical and texture analysis results on both scanners; (3) better image quality evaluation results were obtained between the original (NF) and normalized (N) images, i.e. NF-N, for both scanners, followed by the NF-DS images for the ATL HDI-5000 scanner and the NF-DS on the HDI ATL-3000 scanner; (4) the ATL HDI-5000 scanner images have considerable higher entropy than the ATL HDI-3000 scanner and thus more information content. However, based on the visual evaluation by the two experts, both scanners were rated similarly. The above findings are also in agreement with the visual perception evaluation, carried out by the two vascular experts. The results of this study showed that ultrasound image normalization and speckle reduction filtering are important preprocessing steps favoring image quality, and should be further investigated.

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Section: Discussionmentioning

confidence: 99%

Quality evaluation of ultrasound imaging in the carotid artery based on normalization and speckle reduction filtering

et al. 2006

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“…Furthermore, these filters might optimize the discrimination between blood, myocardium and pericardium. We used the algorithm of Bamber and Daft (1986) (see also Verhoeven and Thijssen 1993) for an assessment study.…”

Section: Preprocessing Of Echographic Imagesmentioning

confidence: 99%

“…Local first-order and second-order statistical parameters that were used are: mean (Bamber and Daft 1986), median (Loupas et al 1989), signal-to-noise ratio (inverse of the coefficient of variation; Verhoeven et al (1991), root-mean-squares (Kotropoulos and Pitas 1992) and mean squares (this paper). For a general assessment of adaptive filtering see Verhoeven and Thijssen (1993). Nonadaptive filtering may be used by using gray level transforms that preserve, or enhance, contour information.…”

Section: Introductionmentioning

confidence: 99%

Segmentation of the Heart Muscle in 3-D Pediatric Echocardiographic Images

Nillesen

Lopata

Gerrits

et al. 2007

Ultrasound in Medicine & Biology

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“…When speckle's size is larger than the filter's size, it remains unaltered (Chen et al 2003). Several adaptive filters were studied (Bamber and Cook-Martin 1987;Bamber and Daft 1986;Bamber and Phelps 1991;Bernstein 1987;Crawford et al 1990Crawford et al , 1993Shankar 1986;Verhoeven and Thijssen 1993). They work well when applied to the uncompressed backscattered envelope signals, but become severely inaccurate with the log-compressed signals.…”

Section: Introductionmentioning

confidence: 97%