Histogram and gray level co-occurrence matrix on gray-scale ultrasound images for diagnosing lymphocytic thyroiditis

Shin, Young Gyung; Yoo, Jeong Seon; Kwon, Hyeong Ju; Hong, Jung Hwa; Lee, Hye Sun; Yoon, Jung Hyun; Kim, Min Jung; Moon, Hee Jung; Han, Kyunghwa; Kwak, Jin Young

doi:10.1016/j.compbiomed.2016.06.014

Cited by 16 publications

(3 citation statements)

References 24 publications

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“…These metrics help detect specific and quantifiable tissue characteristics that are not apparent on a qualitative evaluation of radiological images. Therefore, TA is increasingly used for computer-aided pattern recognition and classification ( 38 ) and has been successfully applied in various contexts in medical imaging ( 39-44 ), including the diagnosis of thyroiditis ( 45 ). The gray level co-occurrence matrix (GLCM) ( 46 ) was generated from the same ROIs that were used for the echogenicity evaluation; these ROIs were analyzed using the free ImageJ plug-in “Texture Analyzer” (v0.4, available at: https://imagej.nih.gov/ij/plugins/texture.html , by Julio E. Cabrera) with the size of the step in pixels set to 1 and the direction set to 0°.…”

Section: Methodsmentioning

confidence: 99%

Altered Thyroid Feedback Loop in Klinefelter Syndrome: From Infancy Through the Transition to Adulthood

Carlomagno

Minnetti

Angelini

et al. 2023

The Journal of Clinical Endocrinology &Amp; Metabolism

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Background and Objectives Thyroid dysfunction has been claimed contributing to the spectrum of Klinefelter syndrome (KS); however, studies are scarce. In a retrospective longitudinal study, we aimed at describing the hypothalamus-pituitary-thyroid (HPT) axis and thyroid ultrasonographic (US) appearance in patients with KS throughout the life span. Methods 254 patients with KS (25.9±16.1 years) were classified according to their pubertal and gonadal status and compared with different groups of non-KS age-matched subjects with normal thyroid function, treated and untreated hypogonadism, or chronic lymphocytic thyroiditis. We assessed serum thyroid hormone levels, anti-thyroid antibodies, US thyroid parameters, in vitro pituitary type 2 deiodinase (D2) expression and activity. Results Thyroid autoimmunity was more prevalent among subjects with KS at all ages, although the Ab negative vs. positive cohorts were not different. Signs of thyroid dysfunction (reduced volume, lower echogenicity, and increased inhomogeneity) were more prominent in KS than in euthyroid controls. Free thyroid hormones were lower in pre-pubertal, pubertal, and adult subjects with KS, while TSH values were only lower in adults. Peripheral sensitivity to thyroid hormones was unaltered in KS, suggesting a dysfunctional HPT axis. Testosterone (T) was the only factor associated with thyroid function and appearance. In vitro testing demonstrated an inhibitory effect of T on pituitary D2 expression and activity, supporting enhanced central sensing of circulating thyroid hormones in hypogonadism. Conclusions From infancy through adulthood, KS is characterized by increased morpho-functional abnormalities of the thyroid gland, combined with a central feedback dysregulation sustained by the effect of hypogonadism on D2 deiodinase.

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Section: Methodsmentioning

confidence: 99%

Altered Thyroid Feedback Loop in Klinefelter Syndrome: From Infancy Through the Transition to Adulthood

Carlomagno

Minnetti

Angelini

et al. 2023

The Journal of Clinical Endocrinology &Amp; Metabolism

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“…Texture features have been shown in several studies to be useful for characterizing and differentiating healthy subjects and neurological patients 64 , 65 . The GLCM, one of the first texture analysis techniques, is a well-established method with several applications, having been successfully used in medical images 66 – 68 . Therefore, we believe texture-based networks might have the potential to do so and even more.…”

Section: Introductionmentioning

confidence: 99%

Texture-based brain networks for characterization of healthy subjects from MRI

da Silveira,

Li,

Castellano

2023

Sci Rep

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Brain networks have been widely used to study the relationships between brain regions based on their dynamics using, e.g. fMRI or EEG, and to characterize their real physical connections using DTI. However, few studies have investigated brain networks derived from structural properties; and those have been based on cortical thickness or gray matter volume. The main objective of this work was to investigate the feasibility of obtaining useful information from brain networks derived from structural MRI, using texture features. We also wanted to verify if texture brain networks had any relation with established functional networks. T1-MR images were segmented using AAL and texture parameters from the gray-level co-occurrence matrix were computed for each region, for 760 subjects. Individual texture networks were used to evaluate the structural connections between regions of well-established functional networks; assess possible gender differences; investigate the dependence of texture network measures with age; and single out brain regions with different texture-network characteristics. Although around 70% of texture connections between regions belonging to the default mode, attention, and visual network were greater than the mean connection value, this effect was small (only between 7 and 15% of these connections were larger than one standard deviation), implying that texture-based morphology does not seem to subside function. This differs from cortical thickness-based morphology, which has been shown to relate to functional networks. Seventy-five out of 86 evaluated regions showed significant (ANCOVA, p < 0.05) differences between genders. Forty-four out of 86 regions showed significant (ANCOVA, p < 0.05) dependence with age; however, the R2 indicates that this is not a linear relation. Thalamus and putamen showed a very unique texture-wise structure compared to other analyzed regions. Texture networks were able to provide useful information regarding gender and age-related differences, as well as for singling out specific brain regions. We did not find a morphological texture-based subsidy for the evaluated functional brain networks. In the future, this approach will be extended to neurological patients to investigate the possibility of extracting biomarkers to help monitor disease evolution or treatment effectiveness.

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“…The six color feature parameters of corneal pupil region images were obtained by the color matrix method[21,22] including Red (R), Green (G), Blue (B), Hue (H), Saturation (S), and Brightness (V). The four texture feature parameters of corneal pupil region images were obtained by gray level co-occurrence matrix method[23], including Contrast (CON), Correlation (COR), Angular Second Moment (ASM), and Homogeneity (HOM). The image feature value taken the average of measured value from five images at each time point.2.3 | Statistical analysisAll data collected of the ten feature parameters were analyzed usingSPSS22.0 (IBM), and the data from Group 1 were used to establish polynomial regression models to analyze the correlation between each feature parameter and PMI.…”

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confidence: 99%

Corneal‐Smart Phone: A novel method to intelligently estimate postmortem interval

Zheng

Huo

Wen

et al. 2020

Journal of Forensic Sciences

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The estimate of postmortem interval (PMI) is one of the most significant and complex research topics in the field of forensic medicine. Finding convenient, objective, and accurate methods to estimate PMI has always been a problem that urgently needs to be solved. Ocular tissues can be stored for a long time during corpse decomposition due to protection of eyelids, orbital wall, and outer dense connective tissue [1]. Therefore, the use of changes in postmortem ocular tissues in determining PMI has been increasingly recognized by scholars [2-4]. The postmortem corneal becomes cloudy and wrinkled over time due to the gradual degeneration and necrosis of corneal cells, irregular thickening of corneal stroma, and water evaporation [5].

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Histogram and gray level co-occurrence matrix on gray-scale ultrasound images for diagnosing lymphocytic thyroiditis

Cited by 16 publications

References 24 publications

Altered Thyroid Feedback Loop in Klinefelter Syndrome: From Infancy Through the Transition to Adulthood

Altered Thyroid Feedback Loop in Klinefelter Syndrome: From Infancy Through the Transition to Adulthood

Texture-based brain networks for characterization of healthy subjects from MRI

Corneal‐Smart Phone: A novel method to intelligently estimate postmortem interval

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