- Tu Trinh
- 0 Comments
- 540 Views
Hospital patients can have catheters and lines inserted during their treatment. For example, severe COVID-19 cases may need endotracheal tubes to support respiration. Serious complications can happen because of a result of malpositioned lines and tubes in patients. Normally, a physician or radiologist must manually check chest x-rays to verify that the lines and tubes are in the optimal position. Not only does this leave room for human error, but delays are also common as radiologists can be busy reporting other scans. Therefore, deep learning algorithms can give a hand to an automatic process of malpositioning detection.
Besides COVID-19 treatment, detection of line and tube position may also help in many popular remedies, such as nasogastric tubes, central venous catheters, or pulmonary artery catheters. This problem arose in Kaggle RANZCR CLiP – Catheter and Line Position Challenge competition. With the help of state-of-the-art of deep learning, Mr. Ngo Do Dang Khoa achieved a Silver medal from the competition.
Speaker: Ngo Do Dang Khoa (KhoaNDD) – FHM.AKAT
Follow us on social media to get most updated news on AI Webinar
