Browsing by Author "Eset, Kubra"

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    Akciğer Tümörlü Hastaların PET ve BT Görüntülerinin Çakıştırılıp Birleştirilmesi
    (IEEE, 2015) Ayyildiz, Oguzhan; Yilmaz, Bulent; Karacavus, Seyhan; Kayaalti, Omer; Icer, Semra; Eset, Kubra; Kaya, Eser
    Image fusion attracts attention in medical field due to complementary behavior and application such as diagnosis and treatment planning. In this study, first positron emission tomography (PET) and computed tomography (CT) images coming from 8 nonsmall cell lung cancer were registered then wavelet and principal component analysis methods were applied to fuse images. According to mutual information metric and nuclear medicine expert wavelet method gave better results when compared to PCA.
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    Citation - Scopus: 1
    Comparison of Lung Tumor Segmentation Methods on PET Images
    (IEEE, 2015) Eset, Kubra; Icer, Semra; Karacavus, Seyhan; Yilmaz, Bulent; Kayaalti, Omer; Ayyildiz, Oguzhan; Kaya, Eser
    Lung cancer is the most common cause of cancer-related deaths that occur all over the world. Recently, various image processing approaches have been used on PET images in order to characterize the uniformity, density, coarseness, roughness, and regularity (i.e., texture properties) of the intratumoral F-18-fluorodeoxyglucose (FDG) uptake. The first and important step of this kind of analysis is to differentiate tumor region from other structures and background, which is called segmentation. In this study, k-means, active contour (snake), and Otsu's tresholding methods were applied on PET images obtained from 36 patients and the performances were compared by the nuclear medicine expert in our team. The results show that Otsu tresholding approach is more selective.