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Gregorius Airlangga
Institut Teknologi Telkom Purwokerto
Computer Science & IT Electrical & Electronics Engineering

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Segmentasi Citra Kanker Payudara Menggunakan K-Means Clustering Berbasis Komputasi Parallel GPU Cuda Andika Elok Amalia; Gregorius Airlangga; Afandi Nur Aziz Thohari
JURNAL INFOTEL Vol 10 No 1 (2018): February 2018
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v10i1.344

Abstract

Image processing technology is now widely used in the health area, one example is to help the radiologist to analyze the result of MRI (Magnetic Resonance Imaging), CT Scan and Mammography. Image segmentation is a process which is intended to obtain the objects contained in the image by dividing the image into several areas that have similarity attributes on an object with the aim of facilitating the analysis process. The increasing amount of patient data and larger image size are new challenges in segmentation process to use time efficiently while still keeping the process quality. Research on the segmentation of medical images have been done but still few that combine with parallel computing. In this research, K-Means clustering on the image of mammography result is implemented using two-way computation which are serial and parallel. The result shows that parallel computing gives faster average performance execution up to twofold.
Co-Authors Afandi Nur Aziz Thohari Andika Elok Amalia