AUTOMATIC COLON SEGMENTATION USING CELLULAR NEURAL NETWORK FOR THE DETECTION OF COLORECTAL POLYPS
Küçük Resim Yok
Tarih
2007
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Istanbul Univ, Fac Engineering
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, an automatic colon segmentation method for Computed Tomography (CT) colonography is presented. Colon segmentation is considered in order to prevent the time consumption while searching polyps out of the colon region and reduce radiologists' interpretation time. The proposed method is the combination of pre-processing and Cellular Neural Networks (CNN). Also recurrent perceptron learning algorithm (RPLA) is used for CNN training. Original CT images are passed through a threshold and then CNN is used to erase unrelated small objects and smooth sharp corners. It is expected automatic colon segmentation will improve the radiologists' diagnostic performance.
Açıklama
Anahtar Kelimeler
Virtual colonoscopy, Segmentation, Colorectal polyp, Cellular Neural Network
Kaynak
Istanbul University-Journal Of Electrical And Electronics Engineering
WoS Q Değeri
N/A
Scopus Q Değeri
Cilt
7
Sayı
2
