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- W4311587295 abstract "Aim: To explore the ability of You Only Look Once version 5 (YOLOv5) to detect and classify breast lesions on dynamic contrast-enhanced MRI. Methods: Four YOLOv5 submodels were examined. A total of 2124 and 2226 images of benign and malignant lesions were obtained, respectively. Precision, recall rate and mean average precision were used to evaluate model performance. Results: The precision (0.916) and mean average precision _0.5 (0.894) of YOLOv5s were higher than those of YOLOv5m (0.832, 0.794), YOLOv5l (0.843, 0.803) and YOLOv5x (0.854, 0.821). In the validation set, YOLOv5s required 1.1 ms to detect lesions per image. Conclusion: YOLOv5s was the fastest and had the highest precision among the four YOLOv5 submodels for the detection and classification of breast lesions on dynamic contrast-enhanced MRI. It has a greater clinical application value.You Only Look Once version 5 (YOLOv5) is the latest YOLO series, which may be a useful tool for detecting and classifying breast lesions on dynamic contrast-enhanced MRI (DCE-MRI) and help clinicians make a rapid, accurate diagnosis and provide treatment. Data were retrospectively collected from a single-center study. The performances of the four submodels (YOLOv5s, YOLOv5m, YOLOv5l and YOLOv5x) were compared. The diagnostic performances of YOLOv5s were comparable with some convolutional neural network models for breast lesion identification in breast ultrasonography and mammography. This study may provide novel insights into the detection and classification of breast lesions on DCE-MRI. Thus, a sufficiently large series of data and high-quality DCE-MRIs are warranted. Owing to its applications in artificial intelligence-assisted imaging diagnosis, this method has promising prospects." @default.
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- W4311587295 date "2022-12-01" @default.
- W4311587295 modified "2023-10-01" @default.
- W4311587295 title "Detection and classification of breast lesions with You Only Look Once version 5." @default.
- W4311587295 doi "https://doi.org/10.2217/fon-2022-0593" @default.
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