Computerized tumor boundary detection using a Hopfield neural network
- 1 January 1997
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Medical Imaging
- Vol. 16 (1), 55-67
- https://doi.org/10.1109/42.552055
Abstract
In this paper, we present a new approach for detection of brain tumor boundaries in medical images using a Hopfield neural network. The boundary detection problem is formulated as an optimization process that seeks the boundary points to minimize an energy functional based on an active contour model. A modified Hopfield network is constructed to solve the optimization problem. Taking advantage of the collective computational ability and energy convergence capability of the Hopfield network, our method produces the results comparable to those of standard "snakes"-based algorithms, but it requires less computing time. With the parallel processing potential of the Hopfield network, the proposed boundary detection can be implemented for real time processing. Experiments on different magnetic resonance imaging (MRI) data sets show the effectiveness of our approach.Keywords
This publication has 12 references indexed in Scilit:
- Using Dynamic Programming For Minimizing The Energy Of Active Contours In The Presence Of Hard ConstraintsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Tracking deformable objects in the plane using an active contour modelIeee Transactions On Pattern Analysis and Machine Intelligence, 1993
- Finite-element methods for active contour models and balloons for 2-D and 3-D imagesIEEE Transactions on Pattern Analysis and Machine Intelligence, 1993
- Optimization neural networks for the segmentation of magnetic resonance imagesIEEE Transactions on Medical Imaging, 1992
- Automatic segmentation of ultrasound images using morphological operatorsIEEE Transactions on Medical Imaging, 1991
- Medical image segmentation by a constraint satisfaction neural networkIEEE Transactions on Nuclear Science, 1991
- Anatomic segmentation and volumetric calculations in nuclear magnetic resonance imagingIEEE Transactions on Medical Imaging, 1989
- Snakes: Active contour modelsInternational Journal of Computer Vision, 1988
- Image Analysis Using Mathematical MorphologyIEEE Transactions on Pattern Analysis and Machine Intelligence, 1987
- Neurons with graded response have collective computational properties like those of two-state neurons.Proceedings of the National Academy of Sciences, 1984