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  • Küçük Resim
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    Adrenal tumor characterization on magnetic resonance images
    (WILEY, 2020) Barstugan, Mucahid.; Ceylan, Rahime.; Asoglu, Semih.; Cebeci, Hakan.; Koplay, Mustafa.
    Adrenal tumors occur on adrenal glands and are generally detected on abdominal area scans. Adrenal tumors, which are incidentally detected, release vital hormones. These types of tumors that can be malignant affect body metabolism. Both of benign and malign adrenal tumors can have a similar size, intensity, and shape, this situation may lead to wrong decision during diagnosis and characterization of tumors. Thus, biopsy is done to confirm diagnosis of tumor types. In this study, adrenal tumor characterization is handled by using magnetic resonance images. In this way, it is wanted that patient can be disentangled from one or more imaging modalities (some of them can includes X-ray) and biopsy. An adrenal tumor image set, which includes five types of adrenal tumors and has 112 benign tumors and 10 malign tumors, was used in this study. Two data sets were created from the adrenal tumor image set by manually/semiautomatically segmented adrenal tumors and feature sets of these data sets are constituted by different methods. Two-dimensional gray-level co-occurrence matrix (2D-GLCM), gray-level run-length matrix (GLRLM), and two-dimensional discrete wavelet transform (2D-DWT) methods were analyzed to reveal the most effective features on adrenal tumor characterization. Feature sets were classified in two ways: benign/malign (binary classification) and type characterization (multiclass classification). Support vector machine and artificial neural network classified feature sets. The best performance on benign/malign classification was obtained by the 2D-GLCM feature set. The best results were assessed with sensitivity, specificity, accuracy, precision, and F-score metrics and they were 99.17%, 90%, 98.4%, 99.17%, and 99.13%, respectively. The highest classification performance on type characterization was obtained by the 2D-DWT feature set as 59.62%, 96.17%, 93.19%, 54.69%, and 54.94% for sensitivity, specificity, accuracy, precision, and F-score metrics, respectively.
  • Küçük Resim
    Öğe
    Experience of using shear wave elastography in evaluation of testicular stiffness in cases of male infertility
    (SPRINGER INTERNATIONAL PUBLISHING AG, 2020) Erdoğan, Hasan.; Durmaz, Mehmet Sedat.; Özbakır, Bora.; Cebeci, Hakan.; Özkan, Deniz.; Gökmen, İbrahim Erdem.
    Purpose The purpose of this study was to determine quantitative testicular tissue stiffness values in normal and infertile men using shear wave elastography (SWE), and to evaluate the relationship between infertility and testicular stiffness value. Methods In total, 100 testes of 50 infertile patients with abnormal semen parameters were classified as group A, and 100 testes of 50 control subjects were classified as group B. These two groups were compared in terms of age, testicular volume, and SWE values. The group B testes were randomly chosen from patients who had applied for ultrasonography for any reason, and who had no testis disease and no history of infertility. Results The mean age of the patients was 27.83 years, and no significant difference in age was found between the groups (P = 0.133). No significant difference in testicular volume was found between the groups (P = 0.672). The SWE values were significantly higher in group A than in group B (P = 0.000 for both m/s and kPa values). SWE values had a negative correlation with mean testicular volume in group A (for m/s values: P = 0.043; for kPa values: P = 0.024). Conclusion SWE can be a useful technique for assessing testicular stiffness in infertile patients to predict parenchymal damage in testicular tissue that leads to an abnormality in sperm quantity. In addition, decreased testicular volume, together with increased SWE values, can reflect the degree of parenchymal damage.