[Research progress on colorectal cancer identification based on convolutional neural network].
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi
; 41(4): 854-860, 2024 Aug 25.
Article
em Zh
| MEDLINE
| ID: mdl-39218614
ABSTRACT
Colorectal cancer (CRC) is a common malignant tumor that seriously threatens human health. CRC presents a formidable challenge in terms of accurate identification due to its indistinct boundaries. With the widespread adoption of convolutional neural networks (CNNs) in image processing, leveraging CNNs for automatic classification and segmentation holds immense potential for enhancing the efficiency of colorectal cancer recognition and reducing treatment costs. This paper explores the imperative necessity for applying CNNs in clinical diagnosis of CRC. It provides an elaborate overview on research advancements pertaining to CNNs and their improved models in CRC classification and segmentation. Furthermore, this work summarizes the ideas and common methods for optimizing network performance and discusses the challenges faced by CNNs as well as future development trends in their application towards CRC classification and segmentation, thereby promoting their utilization within clinical diagnosis.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
/
Neoplasias Colorretais
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Redes Neurais de Computação
Limite:
Humans
Idioma:
Zh
Revista:
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi
Ano de publicação:
2024
Tipo de documento:
Article