Computerized ultrasound B-scan characterization of breast nodules

Lefèbvre, F.; Meunier, Martine; Thibault, Fabienne; Laugier, Pascal; Berger, G.

doi:10.1016/s0301-5629(00)00302-1

Cited by 63 publications

(41 citation statements)

References 21 publications

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“…We adopt the approach considered in [8] in order to assess how the parameter changes over the different ROI locations or sizes. As a measure of its changeability, the classical coefficient of variation (CV, the ratio of the standard deviation to the mean) is used.…”

Section: Parameter Stabilitymentioning

confidence: 99%

Effect of Slice Thickness on Texture-Based Classification of Liver Dynamic CT Scans

Duda

Krȩtowski

Bézy-Wendling

2013

Computer Information Systems and Industrial Management

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Abstract. This paper assesses the impact of slice thickness on texture parameters. Experiments are performed on liver dynamic CT scans, with two slice thicknesses. Three acquisition moments are considered: without contrast, in arterial and in portal phase. In total, 155 texture parameters, extracted with 9 methods, are tested. Classification of normal and cirrhotic liver is performed using a boosting algorithm. Experiments reveal that slice thickness does not considerably influence the stability of the parameters. They also enable to assess the rate of parameter dependency on slice thickness. Finally, they show that applying different slice thicknesses for training and testing the CAD system requires slice thickness-independent parameters.

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Section: Parameter Stabilitymentioning

confidence: 99%

Effect of Slice Thickness on Texture-Based Classification of Liver Dynamic CT Scans

Duda

Krȩtowski

Bézy-Wendling

2013

Computer Information Systems and Industrial Management

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“…Several works [1][2][3] have used the contour delineated by an experienced radiologist, even when computer-aided methods are proposed. However, operator-dependent procedures are highly susceptible to variations [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Breast Ultrasound Segmentation Using Morphologic Operators and a Gaussian Function Constraint

et al. 2008

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-This work proposes a hybrid segmentation method based on Morphological Operators and on a Gaussian function constraint to delimitate the search dominium, both used for tumor segmentation purposes The Watershed operator was also used to find tumor contour. The proposed method was firstly evaluated using gear simulated images (eight and sixteen teeth with different width and height), a power speckle noise of 10% and a contrast ratio of 10:53 referred to the background. The hybrid method was also applied to 200 ultrasound (US) breast images. For assessing the segmentation performance, similarity parameters (overlap ratio, RS, normalized residual mean square value, nrv, and mean distance between contours, dmed) based on the predefined shape or on the US tumor contour depicted by an expert as a gold standard. The segmented contour of the gear simulated images obtained with the hybrid method better preserves the original shape. This finding was evident for both gears, which is particularly important since the teeth mimic contour irregularities. For the US breast images, the proposed method keeps the tumor boundaries without aggregating improper structures, resulting in RS > 50% for 91% of the images, nrv < 40% for 70%, and dmed < 5 pixels for 77% of the cases. These findings suggest that the hybrid method represents more realistically tumor contours, which is a vital diagnosis characteristic.

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“…[10][11][12][13][14][15] Much of this work confirms that it is difficult to precisely classify masses because there is overlap in the acoustic properties of many solid benign and malignant lesions. Computeraided diagnosis with artificial neural networks (ANN), a form of regression analysis, attempts to aid the radiologist in locating suspicious regions that might otherwise be missed 16,17 .…”

Section: Introductionmentioning

confidence: 71%

Statistical analysis to assess automated level of suspicion scoring methods in breast ultrasound

Galperin

2003

Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment

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A well-defined rule-based system has been developed for scoring 0-5 the Level of Suspicion (LOS) based on qualitative lexicon describing the ultrasound appearance of breast lesion. The purposes of the research are to asses and select one of the automated LOS scoring quantitative methods developed during preliminary studies in benign biopsies reduction. The study has used Computer Aided Imaging System (CAIS) to improve the uniformity and accuracy of applying the LOS scheme by automatically detecting, analyzing and comparing breast masses. The overall goal is to reduce biopsies on the masses with lower levels of suspicion, rather that increasing the accuracy of diagnosis of cancers (will require biopsy anyway). On complex cysts and fibroadenoma cases experienced radiologists were up to 50% less certain in true negatives than CAIS. Full correlation analysis was applied to determine which of the proposed LOS quantification methods serves CAIS accuracy the best. This paper presents current results of applying statistical analysis for automated LOS scoring quantification for breast masses with known biopsy results. It was found that First Order Ranking method yielded most the accurate results. The CAIS system (Image Companion ® , Data Companion ® software) is developed by Almen Laboratories and was used to achieve the results.

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Computerized ultrasound B-scan characterization of breast nodules

Cited by 63 publications

References 21 publications

Effect of Slice Thickness on Texture-Based Classification of Liver Dynamic CT Scans

Effect of Slice Thickness on Texture-Based Classification of Liver Dynamic CT Scans

Breast Ultrasound Segmentation Using Morphologic Operators and a Gaussian Function Constraint

Statistical analysis to assess automated level of suspicion scoring methods in breast ultrasound

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