Diagnosis of subarachnoid haemorrhage using heam pigment detection in cerebrospinal fluid: Focus on urine test strips

To accurately detect small defects in urine test strips, the SK-FMYOLOV3 defect detection algorithm is proposed. First, the prediction box clustering algorithm of YOLOV3 is improved. The fuzzy C-means clustering algorithm is used to generate the initial clustering centers, and then, the clustering center is passed to the K-means algorithm to cluster the prediction boxes. To better detect smaller defects, the YOLOV3 feature map fusion is increased from the original three-scale prediction to a four-scale prediction. At the same time, 23 convolutional layers of size 3 × 3 in the YOLOV3 network are replaced with SkNet structures, so that different feature maps can independently select different convolution kernels for training, improving the accuracy of defect classification. We collected and enhanced urine test strip images in industrial production and labeled the small defects in the images. A total of 11634 image sets were used for training and testing. The experimental results show that the algorithm can obtain an anchor frame with an average cross ratio of 86.57, while the accuracy rate and recall rate of nonconforming products are 96.8 and 94.5, respectively. The algorithm can also accurately identify the category of defects in nonconforming products.

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National guidelines for analysis of cerebrospinal fluid for bilirubin in suspected subarachnoid haemorrhage

Annals of Clinical Biochemistry International Journal of Laboratory Medicine ◽

10.1258/000456303322326399 ◽

2003 ◽

Vol 40 (5) ◽

pp. 481-488 ◽

Cited By ~ 35

Author(s):

Keyword(s):

Cerebrospinal Fluid ◽

Subarachnoid Haemorrhage ◽

Lumbar Puncture ◽

Serum Bilirubin ◽

Transport Systems ◽

National Guidelines ◽

Vacuum Tube ◽

Presenting Symptoms ◽

Confounding Variables

It is crucially important to detect subarachnoid haemorrhage (SAH) in all patients in whom it has occurred in order to select patients for angiography and preventative surgery. A computed tomography (CT) scan is positive in up to 98% of patients with SAH presenting within 12h but is positive in only 50% of patients presenting within 1 week. Cerebrospinal fluid (CSF) bilirubin spectrophotometry can be used to determine the need for angiography in those few CT-negative patients in whom clinical suspicion of a SAH remains high; it may remain positive for up to 2 weeks after the event. The lumbar puncture (LP) should only be performed >12h after the onset of presenting symptoms. Whenever possible, collect four sequential CSF specimens. Always ensure that the last CSF sample taken is sent for bilirubin analysis. Protect the CSF from light and avoid vacuum tube transport systems if possible. Always use spectrophotometry in preference to visual inspection. All CSF specimens are precious and should be analysed no matter how they were transported, where necessary with appropriate notice of the caveats regarding oxyhaemoglobin. Centrifuge the specimen at >2000 rpm for 5 min as soon as possible after receipt in the laboratory and in any case within 1 h of collection. Store the supernatant at 4°C in the dark until analysis. An increase in CSF bilirubin is the key finding which supports the occurrence of SAH, but it is not specific for this. In most positive cases bilirubin will occur with oxyhaemoglobin. Oxyhaemoglobin occurring on its own is difficult to interpret and may be increased as a result of in vitro haemolysis of red cells introduced into the CSF during lumbar puncture. This process is exacerbated by vacuum tube transport systems. Results should be interpreted in the light of other investigations (e.g. if scan shows bilirubin then measure serum bilirubin and CSF oxyhaemoglobin and protein) and other confounding variables such as the time elapsed from presentation to LP.

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