#8411. BCHisto-Net: Breast histopathological image classification by global and local feature aggregation

October 2026publication date
Proposal available till 30-05-2025
4 total number of authors per manuscript5500 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Medicine (miscellaneous);
Artificial Intelligence;
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Abstract:
Manual analysis of histopathological images is subjective and prone to human errors. The current state-of-the-art CNN based methods for histopathological image classification can lead to inaccurate diagnosis, as they extract features from the entire image (global features) and overlook the features of the potential regions of interest. The present paper seeks to extract both global and local features required for the accurate classification of breast histopathological images.
Keywords:
Breast cancer; Computer - aided diagnosis; Convolution neural network; Deep learning; Histopathological images; Image analysis; Image classification

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