Name
Title | ||
|---|---|---|
Application of Improved Mask R-CNN Algorithm Based on Gastroscopic Image in Detection of Early Gastric Cancer |
Abstract | ||
|---|---|---|
Gastroscopy is an important step in the diagnosis of early gastric cancer. However, because the morphological manifestations of early gastric cancer are not obvious, endoscopists need long-term specialized training and experience accumulation to correctly identify early cancer through magnification gastroscopy. In this paper, the data set of gastroscopy image is collected and enhanced, and target detection method is combined with gastroscopy image. The Mask R-CNN+BiFPN model was proposed to enhance the feature fusion and improve the detection effect of early gastric cancer lesions. Compared with Mask R-CNN, the improved Mask R-CNN model has better performance, with the sensitivity and specificity of 91.67% and 88.95% in accurately labeled gastroscopic datasets, respectively, showing a good segmentation effect for surface swelling lesions. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/COMPSAC54236.2022.00221 | 2022 IEEE 46TH ANNUAL COMPUTERS, SOFTWARE, AND APPLICATIONS CONFERENCE (COMPSAC 2022) |
Keywords | DocType | Citations |
object detection, gastroscopy images, data enhancement, deep learning | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhi-Heng Cui | 1 | 0 | 0.34 |
| Qin-Yan Zhang | 2 | 0 | 0.34 |
| Jing-Wei Zhang | 3 | 0 | 0.34 |
| Xue Sun | 4 | 0 | 0.34 |
| Qing Wang | 5 | 345 | 76.64 |
| Yi Lei | 6 | 0 | 0.68 |
| Lin Zang | 7 | 0 | 0.34 |
| Li Zhao | 8 | 0 | 0.34 |
| Ji-Jiang Yang | 9 | 232 | 35.53 |