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Related Concept Videos

Endoscopic Procedures IV: Sigmoidoscopy and Laproscopy01:26

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Sigmoidoscopy and laparoscopy are distinct medical procedures that enable physicians to internally inspect different parts of the GI tract. Although they serve different purposes, each is essential for diagnosing and, in some cases, treating various medical conditions.
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An Esophagogastroduodenoscopy (EGD) is a diagnostic procedure in which an endoscopist uses a flexible, lighted endoscope to visualize the upper gastrointestinal (GI) tract. The procedure includes visualizing the oropharynx, esophagus, stomach, and the first part of the small intestine, the duodenum.
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Endoscopic Procedures III: Video Capsule Endoscopy01:28

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Capsule endoscopy, or wireless or video capsule endoscopy, is a diagnostic procedure for examining the entire gastrointestinal tract. Patients swallow a capsule about the size of a vitamin tablet. The capsule is equipped with a transmitter, a battery, an LED light source, and a color video camera to capture images throughout the gastrointestinal tract. This procedure is particularly useful for diagnosing conditions such as Crohn's disease, ulcerative colitis, tumors, polyps, ulcers,...
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Endoscopic Procedures II: Colonoscopy01:25

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Endoscopic Procedures V: ERCP01:26

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Endoscopic Retrograde Cholangiopancreatography (ERCP) is a diagnostic procedure that combines endoscopy and fluoroscopy to diagnose and treat conditions related to the bile ducts, pancreatic ducts, and gallbladder. This procedure is beneficial for identifying and addressing blockages, gallstones, strictures, and tumors within the biliary or pancreatic systems. ERCP is both diagnostic and therapeutic, offering the ability to visualize and treat identified problems in one session.
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This lesson explores three gastrointestinal imaging techniques: radionuclide testing, colonic transit studies, and virtual colonoscopy.
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Related Experiment Video

Updated: May 22, 2025

Author Spotlight: A Reproductive Hysteroscopy Approach for Complete Endometrial Polyp Removal and Enhanced Endometrial Receptivity
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Prompt-based polyp segmentation during endoscopy.

Xinzhen Ren1, Wenju Zhou1, Naitong Yuan1

  • 1Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, CO 200444, China.

Medical Image Analysis
|March 12, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a prompt-based polyp segmentation method (PPSM) using AI and endoscopist eye-tracking data to improve early cancer diagnosis during endoscopy. The PPSM accurately segments polyps, enhancing diagnostic capabilities.

Keywords:
Disposable electronic endoscope with Early-stage cancer auxiliary diagnosisEndoscopists’ gaze attentionPolyp segmentationPrompt

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Gastroenterology

Background:

  • Accurate polyp size identification is vital for endoscopic cancer diagnosis.
  • Indistinct polyp boundaries cause missegmentation and missed diagnoses.
  • Current methods lack efficiency and accuracy in real-world endoscopic scenarios.

Purpose of the Study:

  • To develop a prompt-based polyp segmentation method (PPSM) for enhanced early cancer diagnosis in endoscopy.
  • To integrate endoscopist expertise with AI for improved polyp segmentation.
  • To create a robust and adaptable system for real-time auxiliary diagnosis.

Main Methods:

  • Proposed a prompt-based polyp segmentation network (PPSN) with prompt encoding, feature extraction, and mask decoding modules.
  • Utilized endoscopist ocular attention data (gazes) as prompts to guide segmentation.
  • Implemented non-uniform dot matrix prompts for stability and SAM-based data augmentation for adaptability.

Main Results:

  • The PPSM demonstrated high accuracy and real-time performance in polyp segmentation.
  • Cross-training and cross-testing on multiple datasets confirmed the method's generalization capabilities.
  • Developed a disposable electronic endoscope and image processor with real-time auxiliary diagnosis functionality.

Conclusions:

  • The PPSM effectively combines AI and human expertise for accurate polyp segmentation.
  • The developed system shows significant potential for improving early cancer detection rates during endoscopy.
  • The research facilitates the development of advanced diagnostic tools for gastrointestinal endoscopy.