Automatic liver segmentation in abdomen CT images using SLIC and adaboost algorithms
8th International Conference on Bioscience, Biochemistry and Bioinformatics, ICBBB 2018, Tokyo, Japonya, 18 - 20 Ocak 2018, ss.129-133, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1145/3180382.3180383
- Basıldığı Şehir: Tokyo
- Basıldığı Ülke: Japonya
- Sayfa Sayıları: ss.129-133
- Anahtar Kelimeler: Automatic segmentation, classification, liver, SLIC super-pixel
- Sağlık Bilimleri Üniversitesi Adresli: Evet
Özet
This study is an implementation of liver segmentation on abdomen CT images. The liver organ was segmented by using SLIC super-pixel and AdaBoost algorithms. Firstly, the images were clustered by SLIC super-pixel algorithm. Then, the liver was segmented by AdaBoost classifier. The segmentation process was done automatically. The automatic segmentation is based on the classification of overlapping patches of the image. The results of automatic segmentation and manual segmentation were compared and the efficiency of the method was observed. The best Dice rate was obtained as 92.13% and the best Jaccard rate was obtained as 85.8% on 16 abdomen CT images.