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Wang Z, Gao J, Li M, Zuo E, Chen C, Chen C, Liang F, Lv X, Ma Y. DIEANet: an attention model for histopathological image grading of lung adenocarcinoma based on dimensional information embedding. Sci Rep 2024; 14:6209. [PMID: 38485967 PMCID: PMC10940683 DOI: 10.1038/s41598-024-56355-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 03/05/2024] [Indexed: 03/18/2024] Open
Abstract
Efficient and rapid auxiliary diagnosis of different grades of lung adenocarcinoma is conducive to helping doctors accelerate individualized diagnosis and treatment processes, thus improving patient prognosis. Currently, there is often a problem of large intra-class differences and small inter-class differences between pathological images of lung adenocarcinoma tissues under different grades. If attention mechanisms such as Coordinate Attention (CA) are directly used for lung adenocarcinoma grading tasks, it is prone to excessive compression of feature information and overlooking the issue of information dependency within the same dimension. Therefore, we propose a Dimension Information Embedding Attention Network (DIEANet) for the task of lung adenocarcinoma grading. Specifically, we combine different pooling methods to automatically select local regions of key growth patterns such as lung adenocarcinoma cells, enhancing the model's focus on local information. Additionally, we employ an interactive fusion approach to concentrate feature information within the same dimension and across dimensions, thereby improving model performance. Extensive experiments have shown that under the condition of maintaining equal computational expenses, the accuracy of DIEANet with ResNet34 as the backbone reaches 88.19%, with an AUC of 96.61%, MCC of 81.71%, and Kappa of 81.16%. Compared to seven other attention mechanisms, it achieves state-of-the-art objective metrics. Additionally, it aligns more closely with the visual attention of pathology experts under subjective visual assessment.
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Affiliation(s)
- Zexin Wang
- College of Software, Xinjiang University, Urumqi, 830046, China
| | - Jing Gao
- Xinjiang Key Laboratory of Clinical Genetic Testing and Biomedical Information, Karamay, 834099, China
- Xinjiang Clinical Research Center for Precision Medicine of Digestive System Tumor, Karamay, 834099, China
- Department of Pathology, Karamay Central Hospital, Karamay, 834099, China
| | - Min Li
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
- Key Laboratory of Signal Detection and Processing, Xinjiang University, Urumqi, 830046, China
| | - Enguang Zuo
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
- Xinjiang Cloud Computing Application Laboratory, Karamay, 834099, China
| | - Chen Chen
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
- Xinjiang Cloud Computing Application Laboratory, Karamay, 834099, China
| | - Cheng Chen
- College of Software, Xinjiang University, Urumqi, 830046, China
| | - Fei Liang
- Xinjiang Key Laboratory of Clinical Genetic Testing and Biomedical Information, Karamay, 834099, China
- Xinjiang Clinical Research Center for Precision Medicine of Digestive System Tumor, Karamay, 834099, China
- Department of Pathology, Karamay Central Hospital, Karamay, 834099, China
| | - Xiaoyi Lv
- College of Software, Xinjiang University, Urumqi, 830046, China.
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China.
- Key Laboratory of Signal Detection and Processing, Xinjiang University, Urumqi, 830046, China.
- Xinjiang Cloud Computing Application Laboratory, Karamay, 834099, China.
| | - Yuhua Ma
- Xinjiang Key Laboratory of Clinical Genetic Testing and Biomedical Information, Karamay, 834099, China.
- Xinjiang Clinical Research Center for Precision Medicine of Digestive System Tumor, Karamay, 834099, China.
- Department of Pathology, Karamay Central Hospital, Karamay, 834099, China.
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