Smart Endoscope System | ||||
| The International Undergraduate Research Conference | ||||
| Volume 5, Issue 5, 2021, Page 79-83 PDF (1.38 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/iugrc.2021.245571 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Ahmed Abdel Fattah El-said1; Ahmed Abdel Hakim Abdel Zahir1; Ahmed Reda Abdel Rashid1; Ali Mohammad Ali El-Shamy1; Aida El-Morsi Farhat1; Shrouk Mahmoud Fathy Mahmoud1; Nissreen El-Saber2 | ||||
| 1Zagazig University, Egypt. | ||||
| 2PhD, Zagazig University, Egypt. | ||||
| Abstract | ||||
| As a result of COVID-19 pandemic, doctors face great challenges regarding the operations long duration (e.g. the digestive system ones) and patients face the long waiting list. Unfortunately, most digestive system diseases take time to diagnose. We propose a solution to help clinicians and their patient's diagnosis processes by integrating Artificial Intelligence into medical devices like the endoscope, i.e. a device that enters the human body through its opening ends (e.g. mouth) to allow for a more detailed internal investigation. Smart endoscopes are supported by cameras which are designed to recognize the abnormal tissues in the stomach. Cameras can record certain scenes or take photos of tissues directly to the application. This allows the doctor to explain the observations to the patient and even colleagues. The proposed system supports automatic detection of abnormalities reducing the diagnosis error rate. Therefore, the medical team will be able to conduct a more precise assessment of the internal organs and contribute toward a more accurate diagnosis for the patient's condition. The proposed system takes one step closer towards the advancement of medical technology allowing faster diagnosis reducing the number of misdiagnosed patients or late diagnose due to the long waiting lists. | ||||
| Keywords | ||||
| Medical; Endoscope; AI; Deep Learning; U-Net | ||||
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