RESUMO
Objective:To explore the application value of fetal heart ultrasound image segmentation network model based on knowledge distillation technology in the fine segmentation of fetal heart ultrasound image at three-vessel and trachea (3VT) views.Methods:One thousand and three hundred fetals were retrospectively collected from Sir Run Run Shaw Hospital, Zhejiang University College of Medicine from January 2016 to December 2021, the two-dimensional grayscale ultrasound images of fetal heart at 3VT views were analyzed and then divided into training, validation, and test sets. The training and validation sets were used to construct the auxiliary diagnostic network models, and the test set was used to test the reliability of different network models (U-Net, DeepLabv3+ ). The 3VT views were collected and annotated by an experienced doctor as the reference standard. The intersection over union (IoU), pixel accuracy (PA) and Dice coefficient (Dice) were used as the 3 indexes to evaluate the segmentation accuracy, and the diagnostic efficiency of the training model was evaluated. The training model and the most commonly used segmentation models were identified, and the results were compared. A total of 101 images were randomly selected and assigned to junior doctors, AI and junior doctors assisted AI interpretation. Bland-Altman images were drawn to evaluate their consistency with the reference standard, and the results were compared.Results:The training model of knowledge distillation algorithm achieved better results than U-Net, DeepLabv3+ models on all evaluation indexes, and the average IoU, PA and Dice were 68.6%, 81.4% and 81.3%, respectively. Compared with the U-Net model and DeepLabv3+ model, more accurate segmentation boundaries were obtained by the knowledge distillation algorithm training model, and the quantitative evaluation indexes were improved. With the aid of the model, the diagnostic accuracy of junior doctors was improved.Conclusions:The knowledge distillation algorithm training model segmentation method can identify the anatomical structure of the fetal heart in the 3VT view of the fetal heart ultrasound image, and the recognition result is obviously better than other related methods, and can improve the accuracy of image recognition for doctors with low experience.
RESUMO
Objective: To observe hypoglycemic effects of Yunu Decoction, Zuogui Pill and Shenqi Pill, three compound traditional Chinese herbal medicines, in treatment of diabetes mellitus induced by alloxan in rats, and to compare the therapeutic effects among the three recipes for nourishing yin, clearing away heat, and nourishing yin and warming yang. Methods: Diabetes mellitus was induced in rats with alloxan at a dose of 60 mg/kg via tail vain injection. The diabetic rats were randomly divided into four groups: alloxan model group, Yunu Decoction-treated group, Zuogui Pill-treated group and Shenqi Pill-treated group. Rats in the three recipe groups were administered intragastrically with water extraction of Yunu Decoction, Zuogui Pill, and Shenqi Pill accordingly for 10 days. Then the level of blood glucose was measured by glucose oxidase method and the glucose tolerance was determined. Results: Compared with the normal rats, blood glucose level in the alloxan model group was obviously increased (P<0.05). Glucose levels in the three recipe groups were obviously decreased as compared with the alloxan model group (P<0.05), and glucose level in the Yunu Decoction-treated group after treatment was significant lower than before treatment (P<0.05). The glucose tolerance test indicated that rats in the alloxan model and three recipe groups revealed impaired glucose tolerance as compared with the normal rats, and there were no significant differences between the alloxan model group and the three recipe groups. Conclusion: Yunu Decoction, Zuogui Pill and Shenqi Pill can effectively decrease the glucose level of the rats with diabetes mellitus induced by alloxan, and Yunu Decoction showed the best therapeutic effects. The glucose tolerance test shows that the three recipes cannot correct the abnormal metabolism of glucose.