Czasopismo | PRZEGLĄD ELEKTROTECHNICZNY | Rocznik 2023 - zeszyt 12

Review on Wireless Capsule Endoscopy System Issues, Challenges, and Technologies

Przegląd problemów, wyzwań i technologii związanych z bezprzewodowym systemem endoskopii kapsułkowej

10.15199/48.2023.12.24

nr katalogowy: 146723
10.15199/48.2023.12.24

Streszczenie

The gold standard for diagnosing disorders of the small bowel is wireless capsule endoscopy (WCE). Capsule endoscopy appears to represent the future of effective diagnostic gastrointestinal (GI) endoscopy. As capsule endoscopy doesn't cause any discomfort, it stands a better chance of being adopted by patients than traditional colonoscopy and gastroscopy, making it a good option for detecting cancer or ulcerations. WCE can be helpful in obtaining images of the GI tract from the inside, but pinpointing exactly where the disease is located is still a major challenge. In this paper, reviewing of the studies dealing with the development of the endoscopy capsule and finding techniques and solutions to provide higher efficiency is presented. Also, the paper showed that the tendency to use artificial intelligence (AI) led to an increase in the accuracy of detecting diseases and a decrease in mistakes caused by physicians' lack of attention or fatigue while reading a video from a capsule, as well as the role of artificial intelligence in shortening the time it takes to read the video. When it comes to WCE, deep learning has shown remarkable success in detecting a wide variety of disorders.

Abstract

Złotym standardem w diagnostyce zaburzeń jelita cienkiego jest bezprzewodowa endoskopia kapsułkowa (WCE). Wydaje się, że endoskopia kapsułkowa reprezentuje przyszłość skutecznej endoskopii diagnostycznej przewodu pokarmowego (GI). Ponieważ endoskopia kapsułkowa nie powoduje dyskomfortu, ma większe szanse na przyjęcie przez pacjentów niż tradycyjna kolonoskopia i gastroskopia, co czyni ją dobrą opcją do wykrywania nowotworów czy owrzodzeń. WCE może być pomocne w uzyskiwaniu obrazów przewodu pokarmowego od wewnątrz, ale dokładne określenie lokalizacji choroby nadal stanowi duże wyzwanie. W artykule przedstawiono przegląd badań dotyczących rozwoju kapsuły endoskopowej oraz poszukiwania technik i rozwiązań zapewniających wyższą wydajność. W artykule wykazano również, że tendencja do wykorzystywania sztucznej inteligencji (AI) doprowadziła do zwiększenia dokładności wykrywania chorób i zmniejszenia liczby błędów spowodowanych brakiem uwagi lub zmęczeniem lekarzy podczas czytania wideo z kapsuły, a także Rola sztucznej inteligencji w skróceniu czasu czytania wideo. Jeśli chodzi o WCE, głębokie uczenie się wykazało niezwykły sukces w wykrywaniu szerokiej gamy zaburzeń.

Słowa kluczowe

Keywords

Bibliografia

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