870 research outputs found

    Comparative assessment of texture features for the identification of cancer in ultrasound images: a review

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    In this paper, we review the use of texture features for cancer detection in Ultrasound (US) images of breast, prostate, thyroid, ovaries and liver for Computer-Aided Diagnosis (CAD) systems. This paper shows that texture features are a valuable tool to extract diagnostically relevant information from US images. This information helps practitioners to discriminate normal from abnormal tissues. A drawback of some classes of texture features comes from their sensitivity to both changes in image resolution and grayscale levels. These limitations pose a considerable challenge to CAD systems, because the information content of a specific texture feature depends on the US imaging system and its setup. Our review shows that single classes of texture features are insufficient, if considered alone, to create robust CAD systems, which can help to solve practical problems, such as cancer screening. Therefore, we recommend that the CAD system design involves testing a wide range of texture features along with features obtained with other image processing methods. Having such a competitive testing phase helps the designer to select the best feature combination for a particular problem. This approach will lead to practical US based cancer detection systems which de- liver real benefits to patients by improving the diagnosis accuracy while reducing health care cost

    Influence of the measurement method of features in ultrasound images of the thyroid in the diagnosis of Hashimoto's disease

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    Introduction: This paper shows the influence of a measurement method of features in the diagnosis of Hashimoto's disease. Sensitivity of the algorithm to changes in the parameters of the ROI, namely shift, resizing and rotation, has been presented. The obtained results were also compared to the methods known from the literature in which decision trees or average gray level thresholding are used.Material: In the study, 288 images obtained from patients with Hashimoto's disease and 236 images from healthy subjects have been analyzed. For each person, an ultrasound examination of the left and right thyroid lobe in transverse and longitudinal sections has been performed.Method: With the use of the developed algorithm, a discriminant analysis has been conducted for the following five options: linear, diaglinear, quadratic, diagquadratic and mahalanobis. The left and right thyroid lobes have been analyzed both together and separately in transverse and longitudinal sections. In addition, the algorithm enabled to analyze specificity and sensitivity as well as the impact of sensitivity of ROI shift, repositioning and rotation on the measured features.Results and summary: The analysis has shown that the highest accuracy was obtained for the longitudinal section (LD) with the method of linear, yielding sensitivity = 76%, specificity = 95% and accuracy ACC = 84%. The conducted sensitivity assessment confirms that changes in the position and size of the ROI have little effect on sensitivity and specificity. The analysis of all cases, that is, images of the left and right thyroid lobes in transverse and longitudinal sections, has shown specificity ranging from 60% to 95% and sensitivity from 62% to 89%. Additionally, it was shown that the value of ACC for the method using decision trees as a classifier is equal to 84% for the analyzed data. Thresholding of average brightness of the ROI gave ACC equal to 76%

    Ultrasonographic Evaluation of Diffuse Thyroid Disease: a Study Comparing Grayscale US and Texture Analysis of Real-Time Elastography (RTE) and Grayscale US

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    Background and Objectives : To evaluate and compare the diagnostic performances of grayscale ultrasound (US) and quantitative parameters obtained from texture analysis of grayscale US and elastography images in evaluating patients with diffuse thyroid disease (DTD). Materials and Methods: From September to December 2012, 113 patients (mean age, 43.4±10.7 years) who had undergone preoperative staging US and elastography were included in this study. Assessment of the thyroid parenchyma for the diagnosis of DTD was made if US features suggestive of DTD were present. Nine histogram parameters were obtained from the grayscale US and elastography images, from which ‘grayscale index’ and ‘elastography index’ were calculated. Diagnostic performances of grayscale US, texture analysis using grayscale US and elastography were calculated and compared. Results : Of the 113 patients, 85 (75.2%) patients were negative for DTD and 28 (24.8%) were positive for DTD on pathology. The presence of US features suggestive of DTD showed significantly higher rates of DTD on pathology, 60.7% to 8.2% (p0.05). Conclusion : Diagnostic performances were the highest for grayscale US features in diagnosis of DTD. Grayscale index may be used as a complementary tool to US features for improving sensitivity and NPV.ope

    Ultrasound Elastography

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    The comparison between methods, evaluation of portal hypertension and many other questions are still open issues in liver elastography. New elastographic applications are under evaluation and close to being used in clinical practice. Strain imaging has been incorporated into many disciplines and EFSUMB guidelines are under preparation. More research is necessary for improved evidence for clinical applications in daily practice. The Special Issue published papers on recent advances in development and application of Ultrasound Elastography

    UWOMJ Volume 61, Number 1, December 1991

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    Schulich School of Medicine & Dentistryhttps://ir.lib.uwo.ca/uwomj/1234/thumbnail.jp

    Narrative review of multiparametric ultrasound in parotid gland evaluation

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    Disorders affecting parotid gland represent a heterogeneous group comprising congenital, inflammatory and neoplastic diseases which show a focal or diffuse pattern of appearance. The differentiation of neoplastic from non-neoplastic conditions of parotid glands is pivotal for the diagnostic imaging. Frequently there is evidence of overlapping between the clinical and the imaging appearance of the various pathologies. The parotid gland is also often object of study with the combination of different techniques [ultrasound-computed tomography-magnetic resonance imaging (US-CT-MRI), ex.]. Compared to other dominant methods of medical imaging, US has several advantages providing images in real-time at lower cost, and without harmful use of ionizing radiation and of contrast enhancement. B-mode US, and the microvascular pattern color Doppler are usually used as first step evaluation of parotid lesions. Elastography and contrast-enhanced US (CEUS) has opened further possible perspectives to improve the differentiation between benign and malignant parotid lesions. The characterization of the parotid tumors plays a crucial role for their treatment planning and for the prediction of possible surgical complications. We present, here an updated review of the most recurrent pathologies of parotid gland focusing on the diagnostic power of multiparametric US including CEUS and ultrasound elastography (USE); limitations, advantages and the main key-points will be presented

    Automated Strategies in Multimodal and Multidimensional Ultrasound Image-based Diagnosis

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    Medical ultrasonography is an effective technique in traditional anatomical and functional diagnosis. However, it requires the visual examination by experienced clinicians, which is a laborious, time consuming and highly subjective procedure. Computer-aided diagnosis (CADx) have been extensively used in clinical practice to support the interpretation of images; nevertheless, current ultrasound CADx still entails a substantial user-dependency and are unable to extract image data for prediction modelling. The aim of this thesis is to propose a set of fully automated strategies to overcome the limitations of ultrasound CADx. These strategies are addressed to multiple modalities (B-Mode, Contrast-Enhanced Ultrasound-CEUS, Power Doppler-PDUS and Acoustic Angiography-AA) and dimensions (2-D and 3-D imaging). The enabling techniques presented in this work are designed, developed and quantitively validated to efficiently improve the overall patients’ diagnosis. This work is subdivided in 2 macro-sections: in the first part, two fully automated algorithms for the reliable quantification of 2-D B-Mode ultrasound skeletal muscle architecture and morphology are proposed. In the second part, two fully automated algorithms for the objective assessment and characterization of tumors’ vasculature in 3-D CEUS and PDUS thyroid tumors and preclinical AA cancer growth are presented. In the first part, the MUSA (Muscle UltraSound Analysis) algorithm is designed to measure the muscle thickness, the fascicles length and the pennation angle; the TRAMA (TRAnsversal Muscle Analysis) algorithm is proposed to extract and analyze the Visible Cross-Sectional Area (VCSA). MUSA and TRAMA algorithms have been validated on two datasets of 200 images; automatic measurements have been compared with expert operators’ manual measurements. A preliminary statistical analysis was performed to prove the ability of texture analysis on automatic VCSA in the distinction between healthy and pathological muscles. In the second part, quantitative assessment on tumor vasculature is proposed in two automated algorithms for the objective characterization of 3-D CEUS/Power Doppler thyroid nodules and the evolution study of fibrosarcoma invasion in preclinical 3-D AA imaging. Vasculature analysis relies on the quantification of architecture and vessels tortuosity. Vascular features obtained from CEUS and PDUS images of 20 thyroid nodules (10 benign, 10 malignant) have been used in a multivariate statistical analysis supported by histopathological results. Vasculature parametric maps of implanted fibrosarcoma are extracted from 8 rats investigated with 3-D AA along four time points (TPs), in control and tumors areas; results have been compared with manual previous findings in a longitudinal tumor growth study. Performance of MUSA and TRAMA algorithms results in 100% segmentation success rate. Absolute difference between manual and automatic measurements is below 2% for the muscle thickness and 4% for the VCSA (values between 5-10% are acceptable in clinical practice), suggesting that automatic and manual measurements can be used interchangeably. The texture features extraction on the automatic VCSAs reveals that texture descriptors can distinguish healthy from pathological muscles with a 100% success rate for all the four muscles. Vascular features extracted of 20 thyroid nodules in 3-D CEUS and PDUS volumes can be used to distinguish benign from malignant tumors with 100% success rate for both ultrasound techniques. Malignant tumors present higher values of architecture and tortuosity descriptors; 3-D CEUS and PDUS imaging present the same accuracy in the differentiation between benign and malignant nodules. Vascular parametric maps extracted from the 8 rats along the 4 TPs in 3-D AA imaging show that parameters extracted from the control area are statistically different compared to the ones within the tumor volume. Tumor angiogenetic vessels present a smaller diameter and higher tortuosity. Tumor evolution is characterized by the significant vascular trees growth and a constant value of vessel diameter along the four TPs, confirming the previous findings. In conclusion, the proposed automated strategies are highly performant in segmentation, features extraction, muscle disease detection and tumor vascular characterization. These techniques can be extended in the investigation of other organs, diseases and embedded in ultrasound CADx, providing a user-independent reliable diagnosis

    Relevance of Ultrasound in the Diagnosis and Management of Malignancy of the Thyroid Disorders

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    BACKGROUND: The recent prevalence of ultrasonography has facilitated the early detection and qualitative evaluation of thyroid nodules – to differentiate between thyroid carcinoma and benign nodule, between metastatic lymph node and reactive node. It has moved from the suite of the radiologist to the surgeon’s office. AIM OF THE STUDY: The aim of the present study was to evaluate the relevance of SPUS in the diagnosis and surveillance of malignancy of the thyroid. METHODS: Surgeon performed ultrasound for 389 patients and the data of 350 patients who underwent total thyroidectomy was compared with the report of the RPUS, FNAC and HPE. The sensitivity, specificity, positive predictive value, negative predictive value for each was calculated. The nodule characteristics – echogenicity, margins and calcifications were analysed for correlation with malignancy. CONCLUSIONS: Surgeon who is more familiar with the anatomy and patho-physiology of thyroid disorders triages the nodule better. Multivariate analysis of nodule characteristics showed that heteroechogenicity, irregular margins and microcalcifications had a greater association with DTC after adjustment for the other characteristics
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