#6358. Medical Image Interpolation Using Recurrent Type-2 Fuzzy Neural Network

November 2026publication date
Proposal available till 03-06-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Information Systems;
Software;
Neuroscience (all);
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Abstract:
Image interpolation is an essential process for image processing and computer graphics in wide applications to medical imaging. For image interpolation used in medical diagnosis, the two-dimensional (2D) to three-dimensional (3D) transformation can significantly reduce human error, leading to better decisions. This research proposes the type-2 fuzzy neural networks method which is a hybrid of the fuzzy logic and neural networks as well as recurrent type-2 fuzzy neural networks (RT2FNNs) for advancing a novel 2D to 3D strategy. The ability of the proposed methods in the approximation of the function for image interpolation is investigated.
Keywords:
2D to 3D; artificial intelligence; brain MRI; image interpolation; machine learning; recurrent neural network; type-2 fuzzy system

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