Morphological Detection Of Helicobector Pyloric Organisms On Gastric Mucosa Using Deep Learning Of The Artificial IntelligenceDownload PDF

11 Apr 2018 (modified: 16 May 2018)MIDL 2018 Conference SubmissionReaders: Everyone
  • Abstract: Since discovered, Helicobacter pylori (H. pylori) is acknoledged as one of the major causes of gastric ulcer, duodenal ulcer, gastritis, and gastric cancer. Detecting the infection of H. pylori in human body is of great significance for the treatment of various gastrointestinal diseases caused by Helicobacter pylori. This paper provides a new method of dectecting H. pylori based on digital pathology and deep learning. Through the study of a large number of whole slide images (WSIs), the detection of H. pylori on WSIs from gastric biopsy is achieved. The experimental results in this paper show that this method can achieve good detection performance and has certain promotion and practical value.
  • Keywords: Helicobacter pylori, whole slide image, convolutional neural network, CIFAR-10, Tensorflow
  • Author Affiliation: Guangzhou KingMed Diagnostics, Semptian
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