BraDect: A Novel Brain Tumor Image Classification Algorithm
Authors: 
Chaosheng Tang, Bin Li, Junding SunAuthors Info & Claims
Chaosheng Tang, Bin Li, Junding SunAuthors Info & ClaimsPages 12 - 17
Abstract
Brain tumor is one of the common diseases of the central nervous system, and the incidence and death of brain tumors are among the highest in the world. Although the incidence of brain tumors is lower than that of other systemic tumors, due to the wide range of types and pathological types, the same pathological type is divided into different sub-grades, and has complex imaging manifestations, which makes clinical diagnosis and treatment difficult. In this paper, a new CAD model named BraDect is proposed based on the inducible bias of convolution and the high capacity of Transformer, and the fully connected layer and attention mechanism are improved, which effectively solves the problem of large amount of parameters and low efficiency in the current model. The proposed method had performed SOTA as specificity=99.83%, precision=99.84%, Recall=99.83%, F1 score=99.84%, area under the ROC curve=99%, accuracy=99.28%.
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- BraDect: A Novel Brain Tumor Image Classification Algorithm
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Published In
December 2022
365 pages
ISBN:9781450398039
DOI:10.1145/3579895
Copyright © 2022 ACM.
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Published: 04 April 2023
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ICNCC 2022
ICNCC 2022: 2022 The 11th International Conference on Networks, Communication and Computing
December 9 - 11, 2022
Beijing, China
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