15 research outputs found

    Comparison of Three Different Image Forces for Active Contours on Abdominal Image Boundary Detection

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    Active contour, or snake, is an energy minimizing spline that is useful in image boundary detection. Active contours are stimulated by internal forces, image forces and external forces which maintain the shape of the contours while attract the contours to some desired features, usually edges. Problems in implementing active contours such as convergence and initialization have motivated researchers to modify image forces of the active contours. This paper presents a comparative study among three different image forces: traditional snakes, balloon and gradient vector flow (GVF). The study is validated by experiments on abdominal image boundaries detection. These lead to the conclusion that GVF gives the most appropriate results among the other approaches

    Sebaran Stasioner Pada Sistem Bonus-malus Swiss Serta Modifikasinya (Stationary Distribution of Swiss Bonus-malus System and Its Modification)

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    Bonus-Malus System is a system in actuary that introduce the premium class (state) partition, where the state is influenced by the number of annual claims reported by the policy holder. We could base the determination of the state on the stationary distribution that represent the number of policy holders in any state. Swiss Bonus-Malus System has 22 state. The number of state that involved in this system result in the difficulty of stationary distribution determination. Therefore, the aim of this paper is to study a method to obtain stationary distribution of Swiss Bonus-Malus System by recursive formula, with this recursive formula, the stationary distribution of Swiss Bonus-Malus System can be determined easier. Modification of this system with infinite state result in the changes of recursive formula to obtain the stationary. This changes including the determining of base value of the recursive formula

    Pembuatan Aplikasi Stereogram Generator

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    Di dalam pengolahan citra digital, terdapat banyak cara atau metode untuk menghasilkan suatu citra agar menjadi lebih menarik. Salah satu hasil pengolahan citra tersebut adalah streogram, dimana pengolahan citra jenis ini dapat membuat citra tampak lebih menarik. Hal ini disebabkan citra jenis ini dapat membuat impresi pada otak manusia sebagai obyek tiga dimensi yang keluar dari citra dua dimensi biasa. Pada penelitian ini, dikembangkan aplikasi stereogram generator dengan melakukan penggabungan depth mask dan pattern yang di-input-kan atau dengan menggunakan titik-titik acak yang di-generate secara otomatis. Proses ini dilakukan dengan memindah posisi piksel sesuai dengan gray value pada depth mask

    Lung tumor delineation in PET-CT images using a downhill region growing and a Gaussian mixture model

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    Combined PET-CT is now increasingly used for the clinical evaluation of cancer and is arguably the best tool to stage non-small cell lung cancer (NSCLC). We propose a framework to better delineate lung tumors which utilizes information from PET and CT images. The framework is based on a downhill region growing technique for PET and a Gaussian mixture model for CT images. We applied our framework in 20 PET-CT studies from patients with NSCLC. Experiments show that our method is able to delineate lung tumors in complex cases where the tumors are located near other organs with similar intensities in PET images or when the tumors extends into the chest wall or the mediastinum. We also compared 10 of the datasets with experts performing manual delineation, which produced a volumetric overlapped fraction of 0.78 ± 0.10.Department of Electronic and Information EngineeringRefereed conference pape

    Lung segmentation and tumor detection from CT thorax volumes of FDG PET-CT scans by template registration and incorporation of functional information

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    Automatic segmentation and detection of lungs and tumors in FDG PET-CT images is potentially beneficial in the diagnosis and staging of patients with non-small cell lung cancer (NSCLC). However, simultaneous lung segmentation and tumor detection is not a trivial task, particularly due to noise in the datasets, proximity of the lung lesion to the mediastinum and chest wall in certain instances, and disease involvement of non-enlarged lymph nodes.Department of Electronic and Information EngineeringRefereed conference pape
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