Gökhan Bilgin

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In the diagnosis of preinvasive breast cancer, some of the intraductal proliferations pose a special challenge. The continuum of intraductal breast lesions includes the usual ductal hyperplasia (UDH), atypical ductal hyperplasia (ADH), and ductal carcinoma in situ (DCIS). The current standard of care is to perform percutaneous needle biopsies for diagnosis(More)
This paper presents an unsupervised hyperspectral image segmentation with a new subtractive-clustering-based similarity segmentation and a novel cluster validation method using one-class support vector (SV) machine (OC-SVM). An estimation of the correct number of clusters is an important task in hyperspectral image segmentation. The proposed cluster(More)
In this work, classification of cellular structures in the high resolutional histopathological images and the discrimination of cellular and non-cellular structures have been investigated. The cell classification is a very exhaustive and time-consuming process for pathologists in medicine. The development of digital imaging in histopathology has enabled the(More)
Computerized analysis of Doppler ultrasound signals can aid early detection of asymptomatic circulating emboli. For analysis, physicians use informative features extracted from Doppler ultrasound signals. Time -frequency analysis methods are useful tools to exploit the transient like signals such as Embolic signals. Detection of discriminative features(More)
In this work, improvement of final segmentation results is aimed by evaluating spatial relations in the segmentation of histopathological images. In the first step features are extracted using Haralick texture descriptor in the La*b* color space for pre-segmentation of histopathological images. Some training sets with different number of samples are(More)
This letter presents unsupervised hyperspectralimage classification based on fuzzy-clustering algorithms that spatially exploit membership relations. Not only is the conventional fuzzy c-means approach used to demonstrate the advantage of using membership relations but also Gustafson–Kessel clustering, which uses an adaptive distance norm, is, for the first(More)
Hepatodiaphragmatic interposition of the intestine, known as Chilaiditi’s syndrome, is a rare and often asymptomatic anomaly, typically found as an incidental radiographic sign. We report a case of Chilaiditi’s syndrome associated with transverse colon volvulus, predisposed by segmental agenesis of the right lobe of the liver. A 45-year-old man presented(More)
In this work, segmentation of cellular structures in the high resolutional histopathological images and possibility of the discrimination within normal and mitotic cells has been investigated. Mitosis detection is very exhaustive and time consuming process. In the first step, features of cells which have been found by the clustering algorithm have been(More)
Automated analysis of electrocardiography (ECG) signals compose a system for early detection of heart disorders. One of the most important parts of ECG signal classification system is to produce the discriminative features for proper identification of heart disorders. Fractional Fourier Transform (FrFT) as the generalized form of Fourier Transform (FT)(More)
In this work, cellular mitosis detection in histopathological images has been investigated. Mitosis detection is very expensive and time consuming process. Development of digital imaging in pathology has enabled reasonable and effective solution to this problem. Segmentation of digital images provides easier analysis of cell structures in histopathological(More)