Abdominal CT images have been widely studied in the recent years as they are becoming an invaluable mean for abdominal organ investigation. In the field of medical image processing, some of the current interests are the automatic diagnosis of liver pathologies and its 3D volume rendering. The first and fundamental step in all these studies is the automatic liver segmentation, that is still an open problem. In this paper we describe an automatic method to segment the liver from abdominal CT data, by combining an α-expansion and a graph cut algorithm. When evaluated on the data of 40 patients, by comparing the automatically detected liver volumes to the liver boundaries manually traced by three experts, the method achieves a symmetric volume difference of 94%.
3D α-expansion and graph cut algorithms for automatic liver segmentation from CT images / E. Casiraghi, G. Lombardi, S. Pratissoli, S. Rizzi - In: Knowledge-based intelligent information and engineering systems: KES 2007 - WIRN 2007 : 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Vietri sul Mare, Italy, September 12 - 14, 2007 ; proceedings / [a cura di] B. Apolloni, R.J. Howlett, L. Jain. - Berlin : Springer, 2007. - ISBN 978-3-540-74817-5. - pp. 421-428 (( Intervento presentato al 11. convegno International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES) tenutosi a Vietri sul Mare nel 2007 [10.1007/978-3-540-74819-9_52].
3D α-expansion and graph cut algorithms for automatic liver segmentation from CT images
E. Casiraghi;G. Lombardi;S. Pratissoli;
2007
Abstract
Abdominal CT images have been widely studied in the recent years as they are becoming an invaluable mean for abdominal organ investigation. In the field of medical image processing, some of the current interests are the automatic diagnosis of liver pathologies and its 3D volume rendering. The first and fundamental step in all these studies is the automatic liver segmentation, that is still an open problem. In this paper we describe an automatic method to segment the liver from abdominal CT data, by combining an α-expansion and a graph cut algorithm. When evaluated on the data of 40 patients, by comparing the automatically detected liver volumes to the liver boundaries manually traced by three experts, the method achieves a symmetric volume difference of 94%.
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