CT image segmentation of meat sheep Loin based on deep learning.

There are no clear boundaries between internal tissues in sheep Computerized Tomography images, and it is difficult for traditional methods to meet the requirements of image segmentation in application. Deep learning has shown excellent performance in image analysis. In this context, we investigated the Loin CT image segmentation of sheep based on deep learning models. The Fully Convolutional Neural Network (FCN) and 5 different UNet models were applied in image segmentation on the data set of 1471 CT images including the Loin part from 25 Australian White rams and Dolper rams using the method of 5-fold cross validation. After 10 independent runs, different evaluation metrics were applied to assess the performances of the models. All models showed excellent results in terms evaluation metrics. There were slight differences among the results from the six models, and Attention-UNet outperformed others methods with 0.998±0.009 in accuracy, 4.391±0.338 in AVER_HD, 0.90±0.012 in MIOU and 0.95±0.007 in DICE, respectively, while the optimal value of LOSS was 0.029±0.018 from Channel-UNet, and the running time of ResNet34-UNet is the shortest.

Cardiac multi-marker strategy for effective diagnosis of acute myocardial infarction.

BACKGROUND: Heart-type fatty acid-binding protein (H-FABP) is a heart-specific and highly sensitive biomarker for early diagnosis of acute myocardial infarction (AMI). We investigated the effectiveness of H-FABP for diagnosis of AMI in patients with different ethnic background and different time from symptom onset. METHODS: Venous blood was withdrawn from consecutive patients with acute chest pain admitted to the First Affiliated Hospital of Xinjiang Medical University. The blood samples were used for measurement of creatine kinase MB (CK-MB) and cardiac troponin I (cTnI) using Beckman Coulter DC-800 analyzer, and detection of H-FABP using a one-step bedside immunotest. RESULTS: Two hundred and eighty-nine patients admitted within 12h after the onset of symptoms were recruited in the study. The H-FABP immunotest was found to have higher diagnostic accuracy than cTnI and CK-MB in patients admitted within 3h. The combination of H-FABP and cTnI was found to have the highest diagnostic accuracy (91%) among different cardiac markers and the other combinations. It gave the highest sensitivity [96% (95% CI: 91-98%)] and a comparable specificity [84% (95% CI: 76-89%)] to cTnI alone. CONCLUSION: A cardiac panel consisting of H-FABP and troponin is recommended.