Hibaszűrés nagy felbontású nyelőcső manometriában gépi tanulás segítségével

Error filtering in high resolution esophageal manometry using machine learning

Szerzők

  • CZAKO Zoltán
  • SEBESTYEN Gheorghe
  • HANGAN Anca

Kulcsszavak:

probe positioning, high resolution esophageal manometry, machine learning, szonda pozicionálás, nagy felbontású nyelőcső manometria, gépi tanulás

Absztrakt

In this paper we present a Machine Learning based solution for detecting probe positioning failures in High Resolution Esophageal Manometry images, which can be used before applying the Chicago Classification [1] algorithm, this way maximizing the precision of the esophageal motility diagnosis.

Kivonat

Ebben a cikkben egy gépi tanuláson alapuló megoldást mutatunk be a szonda pozicionálási hibáinak észlelésére nagy felbontású nyelőcső manometria képeken, amely felhasználható a Chicago osztályozási algoritmus [1] alkalmazása előtt, így maximalizálva a nyelőcső motilitás diagnózisának pontosságát.

Hivatkozások

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Megjelent

2021-10-11