Class Mamba: Classified Mamba for Polyp Classification
Abstract
or even decades for polyps to develop into colorectal cancer. Therefore, distinguishing between malignant and benign lesions is of great
clinical significance for early detection and treatment, and it can also help patients avoid excessive medical costs as much as possible.
However, due to the diverse morphologies and ambiguous boundaries of polyps, accurate classification of polyps has become a huge challenge. Recently, state space models represented by Mamba have overcome the shortcomings of convolutional neural network (CNN) in
global modeling ability and the problem of quadratic computational complexity existing in Transformer. Therefore, based on Mamba, this
paper proposes a model named ClassMamba. The application of the model in this paper to the classification of polyps shows strong competitiveness.
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DOI: http://dx.doi.org/10.70711/mhr.v2i7.7448
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