Quantitative evaluation of diagnostic information around the contours in ultrasound images

Ito, Masayasu; Chono, Tomoaki; Sekiguchi, Megumu; Shiina, Tsuyoshi; Mori, Hiromu; Tohno, Eriko

doi:10.1007/s10396-005-0050-2

Cited by 9 publications

(7 citation statements)

References 13 publications

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“…[3][4][5][6][7][8][9][10] Computerized schemes and CAD methods for evaluating ultrasound images can reduce dependency on the operator, provide a more objective interpretation of ultrasound findings, and improve the diagnostic accuracy of radiologists. 11 Various computerized features have been extracted from breast ultrasound images and have been used to assess the malignancy of breast tumors.…”

Section: Introductionmentioning

confidence: 99%

Partial dependence of breast tumor malignancy on ultrasound image features derived from boosted trees

Yang

Zhang

et al. 2010

J. Electron. Imaging

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Various computerized features extracted from breast ultrasound images are useful in assessing the malignancy of breast tumors. However, the underlying relationship between the computerized features and tumor malignancy may not be linear in nature. We use the decision tree ensemble trained by the cost-sensitive boosting algorithm to approximate the target function for malignancy assessment and to reflect this relationship qualitatively. Partial dependence plots are employed to explore and visualize the effect of features on the output of the decision tree ensemble. In the experiments, 31 image features are extracted to quantify the sonographic characteristics of breast tumors. Patient age is used as an external feature because of its high clinical importance. The area under the receiver-operating characteristic curve of the tree ensembles can reach 0.95 with sensitivity of 0.95 ͑61/ 64͒ at the associated specificity 0.74 ͑77/ 104͒. The partial dependence plots of the four most important features are demonstrated to show the influence of the features on malignancy, and they are in accord with the empirical observations. The results can provide visual and qualitative references on the computerized image features for physicians, and can be useful for enhancing the interpretability of computer-aided diagnosis systems for breast ultrasound.

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Section: Introductionmentioning

confidence: 99%

Partial dependence of breast tumor malignancy on ultrasound image features derived from boosted trees

Yang

Zhang

et al. 2010

J. Electron. Imaging

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“…The prevalence of thyroid nodules in population is increasing around the world. In China, the morbidity of thyroid cancer grows gradually from year to year, especially in female patients [ 1 – 3 ]. Recently, the estimated incidence of thyroid nodules is nearly 19–67%, approximately 5–15% of these nodules are found to be malignant [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

A novel TIRADS of US classification

et al. 2018

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BackgroundThyroid imaging reporting and data system (TIRADS) is the assessment of a risk stratification of thyroid nodules, usually using a score. However, there is no consensus as to the version of TIRADS for reporting the results of thyroid ultrasound in clinic. The objective of this study is to develop a practical TIRADS with which to categorize thyroid nodules and stratify their malignant risk.MethodsA TIRADS scoring system was developed to provide more decision levels than standard scoring through the selection of the ultrasound features which include the calcification shape, margins, taller-than-wide, internal echo, blood flow quantization of features, setting of the weight, and calculation of the score. Ultimately, the accuracy of our TIRADS was evaluated by comparing with the results of current vision of TIRADS and thyroid radiologist in 153 patients who had US-guided fine-needle aspiration biopsy.ResultsClassification results showed that the total accuracy reached 97% (100% of malignant and 95% of the benign) in 153 cases (benign:78, malignant:75). The percentages of malignancy is defined in our TIRADS were as follows: TIRADS 2 (0% malignancy), TIRADS 3 (3.6% malignancy), TIRADS 4 (17–75% malignancy), and TIRADS 5 (98% malignancy).ConclusionsWe established a novel TIRADS to predict the malignancy risk of the thyroid nodules based on six categories US features by a scoring system, which included a standardized vocabulary and score and a quantified risk assessment. The results showed that objective quantitative classification of thyroid nodules by our TIRADS can be useful in guiding management decisions.

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“…In ultrasound tissue characterization based on the characteristics of the echo signal such as power spectrum, texture parameters, local attenuation, and statistical characteristics, it is assumed that changes in tissue properties such as attenuation and elasticity are uniform in the liver, and a single evaluation index is therefore used in many methods [10][11][12][13][14][15][16][17]. Our group also quantified liver fibrosis by analyzing the echo amplitude envelope [18][19][20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Proposal of a parametric imaging method for quantitative diagnosis of liver fibrosis

Yamaguchi

Hachiya

2010

J Med Ultrasonics

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Quantitative evaluation of diagnostic information around the contours in ultrasound images

Abstract: In many ultrasound images of breast tumors, the combined techniques, the variance ratio of the logarithmic K distribution to the logarithmic Rayleigh distribution and the multilevel technique with local image information can effectively extract abnormal tissue contours.

Cited by 9 publications

References 13 publications

Partial dependence of breast tumor malignancy on ultrasound image features derived from boosted trees

Partial dependence of breast tumor malignancy on ultrasound image features derived from boosted trees

A novel TIRADS of US classification

Proposal of a parametric imaging method for quantitative diagnosis of liver fibrosis

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