Artificial neural network based abdominal organ segmentations: A review


Goceri E., MARTINEZ E.

IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015, Florida, United States Of America, 9 - 11 December 2015, pp.1191-1194 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/icmla.2015.231
  • City: Florida
  • Country: United States Of America
  • Page Numbers: pp.1191-1194
  • Keywords: Organ segmentation, neural networks, MR images, CT images, IMAGES, SERIES
  • Akdeniz University Affiliated: Yes

Abstract

There are many neural network based abdominal organ segmentation approaches from medical images. Computed tomography images were mostly used in these approaches. Applied techniques are usually based on prior information regarding position, shape, and size of organs in these methods. In the literature, there are only a few neural network based techniques that were implemented to segment abdominal organs from magnetic resonance based images. In this paper, we present these methods and their results.

© 2015 IEEE.There are many neural network based abdominal organ segmentation approaches from medical images. Computed tomography images were mostly used in these approaches. Applied techniques are usually based on prior information regarding position, shape, and size of organs in these methods. In the literature, there are only a few neural network based techniques that were implemented to segment abdominal organs from magnetic resonance based images. In this paper, we present these methods and their results.