Segmentation of medical images by using k-NN classifier on field programmable logic array (FPGA)
Küçük Resim Yok
Tarih
2010
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Image segmentation is one of the mostly used procedures in the medical image processing applications. Due to the high resolution characteristic of the medical images and a large amount of computational load in mathematical methods, medical image segmentation process has an excessive computation complexity. Recently, Field Programmable Gate Array (FPGA) implementation capable of performing many complex computations in parallel has been applied in many areas needed for high computation time. In this study, it is proposed that neigbour-pixel-intensity based feature extraction methods for extraction of the textural features in medical images, and k-NN classifier for segmentation process.
Açıklama
2010 7th National Conference on Electrical, Electronics and Computer Engineering, ELECO 2010 -- 2 December 2010 through 5 December 2010 -- Bursa -- 83834
Anahtar Kelimeler
Classifiers, Electrical engineering, Feature extraction, Field programmable gate arrays (FPGA), Medical imaging, Complex computation, Computation complexity, Computation time, Computational loads, Feature extraction methods, Field programmable logic, Field-programmable gate array implementations, High resolution, Intensity-based, k-NN classifier, Mathematical method, Medical Image Processing, Medical image segmentation, Medical images, Segmentation process, Textural feature, Image segmentation
Kaynak
2010 National Conference on Electrical, Electronics and Computer Engineering, ELECO 2010
WoS Q Değeri
Scopus Q Değeri
N/A
