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Item Intraosseous angiolipoma of the frontal bone with a unique location: A clinical and pathological case illustration and review of the literature(2014) Atilgan, Alev Ok; Terzi, Aysen; Agildere, Muhtesem; Caner, Hakan; Ozdemir, B. HandanHere, we report a case of a 16-year-old female patient was referred with scalp swelling and headache. Her neurological examination was normal and imaging of the skull revealed a well-defined lytic lesion measuring 15 mm x 6 mm to the right of the frontal bone. She was operated on with a prediagnosis of Langerhans cell histiocytosis. A wide excision with negative margins was made and the defect was reconstructed with a titanium plate. Subsequently, the lesion was histopathologically diagnosed as an angiolipoma of the frontal bone. The postoperative period was uneventful and she remained well during 1-year follow-up with no evidence of recurrence. Angiolipomas are rare benign lipomatous lesions located mostly in subcutaneous tissue of the forearm or trunk and frequently occur before puberty or in young adults. They are not common in bones. To the best of our knowledge, this is the first angiolipoma of the frontal bone reported.Item Monitoring nodule progression in chest X-ray images(2018) Sumer, Emre; Engin, Muharrem; Agildere, Muhtesem; Ogul, HasanLung nodules are frequently observed in cases of cancer. Nodules can be monitored with technologies such as computed tomography (CT) or magnetic resonance imaging (MRI). However. x-ray imaging is a low-cost method as well as its widespread usage. In this context, monitoring the nodules in short intervals by x-ray imaging gives benefits in many aspects. In this study, a three-stage novel approach is proposed to trace the nodule progressions from the lung x-ray images, automatically. In the first stage, x-ray images of a patient taken at different times must be registered to evaluate the nodule progression. To perform the registration, feature extraction and matching methods are employed, and then the homography matrix is calculated. In the second stage, according to previously known nodule positions, matched nodules are detected on registered images. Mismatched nodules in the first image are considered as lost, while the nodules only found in the second image are evaluated as newly appeared. In the last stage, nodules are considered as closed contours consisting of pixel set where closed contour area is calculated after nodule matching process. In this way, growth and shrink states are determined numerically. To test the proposed approach, a patient data set provided by Baskent University, Department of Radiology is used. The validation of the test results is performed by an expert radiologist According to the results obtained, the presented nodule progression trace system is found promising.