Anatomic landmarks detection by deep learning in colonoscopy
International medical recommendations are indicating the landmark positions that have to
be reached for a valid colonoscopy examination. In this preliminary study we compared
several pre-trained deep learning neural structures, given the task of retraining for
identification in real-time of four out of nine such important positions. We have improved the
training dataset of colonoscopy frames three times to finally get successful results. Our trials
were made using a Jetson Xavier NX developing microsystem.
be reached for a valid colonoscopy examination. In this preliminary study we compared
several pre-trained deep learning neural structures, given the task of retraining for
identification in real-time of four out of nine such important positions. We have improved the
training dataset of colonoscopy frames three times to finally get successful results. Our trials
were made using a Jetson Xavier NX developing microsystem.
Anatomic Landmarks Detection by Deep Learning in Colonoscopy
International medical recommendations are indicating the landmark positions that have to
be reached for a valid colonoscopy examination. In this preliminary study we compared
several pre-trained deep learning neural structures, given the task of retraining for
identification in real-time of four out of nine such important positions. We have improved the
training dataset of colonoscopy frames three times to finally get successful results. Our trials
were made using a Jetson Xavier NX developing microsystem.
be reached for a valid colonoscopy examination. In this preliminary study we compared
several pre-trained deep learning neural structures, given the task of retraining for
identification in real-time of four out of nine such important positions. We have improved the
training dataset of colonoscopy frames three times to finally get successful results. Our trials
were made using a Jetson Xavier NX developing microsystem.
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