Understanding the process of quantitative ultrasonic tissue characterization.

Allison, Janice W.; Barr, Lori L.; Massoth, R. J.; Berg, G. P.; Krasner, Brian; Garra, Brian S.

doi:10.1148/radiographics.14.5.7991816

Cited by 23 publications

(19 citation statements)

References 17 publications

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“…Visual inspection of US images is limited by the ability of the human eye to detect subtle changes in tissue echogenicity, which can lead to underestimation of mild white matter lesions. One of the methods used to quantitatively measure sonographic data is textural feature analysis; this approach has been useful for identifying diffuse diseases of the liver (Allison et al 1994;Sun et al 1996). Several authors (Barr et al 1996;Simaeys et al 2000;Vansteenkiste et al 2005;Hope et al 2008) have attempted to reliably quantify neonatal brain lesions; however, a practical method for routine use in clinical practice remains to be established.…”

Section: Introduction and Literaturementioning

confidence: 99%

Quantitative Tissue Echogenicity of the Neonatal Brain Assessed by Ultrasound Imaging

Padilla

Enríquez

Jansson

et al. 2009

Ultrasound in Medicine & Biology

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Section: Introduction and Literaturementioning

confidence: 99%

Quantitative Tissue Echogenicity of the Neonatal Brain Assessed by Ultrasound Imaging

Padilla

Enríquez

Jansson

et al. 2009

Ultrasound in Medicine & Biology

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“…Conventional B-mode ultrasound images are formed by transmitting an acoustic pulse into the body, followed by receipt, processing and display of the amplitude of returning echo signals. Unfortunately, not all of this information is detectable with the human eye on hard copy or in real-time B-mode image [18]. This drawback has prompted investigations to search for other ways to process echo signals and obtain quantitative ultrasonographic data from tissues [19].…”

Section: Discussionmentioning

confidence: 99%

“…It was found that these measurable acoustic properties depend on cell size, the material between cells and the ultrastructure [18]. The texture analysis was used in a number of anatomical sites in the human body, including precision of breast pathologies and hepatic steatosis [20,21].…”

Section: Discussionmentioning

confidence: 99%

Quantitative Sonographic Differences in Mid-Urethra between Postmenopausal Women with and without Stress Urinary Incontinence

Olgan

Mantar

Okyay

et al. 2016

Gynecol Obstet Invest

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Aim: The aim of this study was to evaluate midurethral tissue characteristics in continent and stress urinary incontinent postmenopausal women by using transvaginal ultrasound gray-level histogram. Methods: Thirty-seven patients with stress urinary incontinence (SUI) and 77 patients without SUI were evaluated. Vaginal ultrasound gray-level histograms were performed by 2 gynecologists blinded to patients' SUI statuses. The mean gray-level (MGL) of ultrasound gray-level histogram, representing the echogenicity of a region of interest, was measured in the anterior and posterior midurethral wall along a vertical ultrasound beam. The difference in MGL between anterior and posterior (AP difference) midurethra was calculated. Results: The MGL value of SUI patients was found to be lower in posterior (p = 0.008) and higher in anterior midurethral region (p = 0.001) when compared with control group. In addition, the difference in MGL between anterior and posterior midurethra (AP difference) was found to be higher in SUI group (p < 0.001). Multivariate analysis by logistic regression including confounding factors revealed that AP difference was independently associated with presence of SUI (adjusted OR 1.14, 95% CI 1.08-1.20, p < 0.001). Intra- and inter-observer reproducibility was found to be high with intraclass correlation coefficient of 0.83 and 0.78, respectively. Conclusion: Postmenopausal SUI patients might have a distinct midurethral echogenicity pattern with the quantitative ultrasonography.

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“…1). These parameters were defined GÜLTİKEN, KANCA, GÜNEN, KUTSAL, EMRE, EVANGELOS, ASLAN by Allison et al [26] and Moss et al [27] as: Mean Gray Level (Arithmetical average grey level of all pixels in picture, defines the brightness), Mean Gradient (Variations in grey values of neighbor pixels, defines microtexture of sample), Homogeneity (Uniformity of grey value combination of neighbor pixels in defined matrix, defines either micro-or macrotexture of sample), Entropy (A measure of the uniformity of matrix values), Contrast (A measure of how many large grey-level differences are present in the ROI), Gray Value (The brightness of pixels in a digitized image).…”

Section: Animal Grouping and Image Acquisitionmentioning

confidence: 99%

Köpek Meme Tümörlerinde B-Mode Ekodesen Analizi ve Renkli Doppler Ultrasonografi

Mülazimoğlu¹,

Beceriklisoy²,

Schäfer-Somi³

et al. 2016

Kafkas Univ Vet Fak Derg

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Forty-one mammary gland tumors from twenty eight bitches were used for the study. Ultrasonographic examinations of tumor masses were performed before surgical excision and a quadratic region-of-interest (ROI) was chosen randomly on B-mode tumor images for the echotexture analyses. All tumors were evaluated histopathologically after surgery. Contrast (CONT), Mean Gradient (MG), Mean Value (MV), Homogeneity (HOM), Entropy (ENTR) and Gray Value (GV) parameters were used for the texture analyses of ultrasonographic images. Ultrasonographic image characteristics were additionally evaluated by the following macroscopic patterns: tumor shape, invasion of tumor to surrounding tissue, tumor border sharpness, echogenicity of tumor, hyperechogenic artifact, anechogenic artifact, and shadow around tumor. After B-mode ultrasonographic examination, Pulsatility Index (PI), Resistive Index (RI), Peak Systolic Flow Velocity (Vmax) and Number of Color Pixel (CP) parameters were evaluated by means of color Doppler sonography. Statistical analysis of the HOM and GV parameters indicated that there was a significant difference between benign (3.10 and 1.14) and malignant tumors (1.54 and 0.57; P<0.01). Besides, a significant difference was found between images of MalignantMixed Tumors (MMT) and Benign-Mixed Tumors (BMT) with regard to CONT and HOM (p< 0.001). In addition, MV was significantly higher in malignant tumors in comparison to the benign cases (P<0.05). A significant negative correlation was found between tumor size and MV in malignant tumor and adenocarcinoma cases (-0.991/ P<0.05; -0.999/P<0.01, respectively). On the other hand, there was a positive correlation between tumor size and GV (0.961/P<0.05) in malignant tumors. Keywords

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Understanding the process of quantitative ultrasonic tissue characterization.

Cited by 23 publications

References 17 publications

Quantitative Tissue Echogenicity of the Neonatal Brain Assessed by Ultrasound Imaging

Quantitative Tissue Echogenicity of the Neonatal Brain Assessed by Ultrasound Imaging

Quantitative Sonographic Differences in Mid-Urethra between Postmenopausal Women with and without Stress Urinary Incontinence

Köpek Meme Tümörlerinde B-Mode Ekodesen Analizi ve Renkli Doppler Ultrasonografi

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