In the clinical stage, suspected hemolytic plasma may cause hemolysis illness, manifesting as symptoms such as heart failure, severe anemia, etc. Applying a deep learning method to plasma images significantly improves recognition accuracy, so that this paper proposes a plasma quality detection model based on improved "You Only Look Once" 5th version (YOLOv5). Then the model presented in this paper and the evaluation system ‌were introduced‌ into the plasma datasets, and ‌the average accuracy of the final classification reached 98.7%‌. The results of this paper's experiment were obtained through the combination of several key algorithm modules including‌ omni-dimensional dynamic convolution, pooling with separable kernel attention, residual bi-fusion feature pyramid network, ‌and‌ re-parameterization convolution. The method of this paper‌ obtains the feature information of spatial mapping efficiently, and enhances the average recognition accuracy of plasma quality detection. This paper presents a high-efficiency detection method for plasma images, aiming to provide a practical approach to prevent hemolysis illnesses caused by external factors.
Algorithms ; Humans ; Hemolysis ; Plasma ; Deep Learning ; Image Processing, Computer-Assisted/methods*

In order to meet the needs of the flow cytometry for the simultaneous analysis of multiple fluorescence wavelengths and small volume, the design method of flow cytometry spectrum analysis system is presented by analyzing the characteristics of Dyson structure. And according to the method, a flow cytometry spectrum analysis system is disigned with Dyson type.The system's spectral range is 400 nm to 800 nm, the defocused spot size is less than the pixel size 24μ mm, the ransfer function value is above 0.8 at the Nyquist cut-off frequency 21 lp/mm,the spectral resolution is less than 3 nm, and the overall size is 83.54 mm×85.60 mm.The system has good optical performance and small volume, which meets the needs of the flow cytometry fluorescence spectral analysis. The outstanding innovation of this system is the application of Dyson light splitting structure and EMCCD detector which is high speed and high sensitivity.
Equipment Design ; Flow Cytometry ; instrumentation