Clinical trial · Observational
EndoStyle: Artificial Intelligence Image Transformation Tool for Colonoscopy
EndoStyle: Survey of Physicians on Endoscopic Image Style Transfer.
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
The study addresses the limitations of current AI systems in gastrointestinal endoscopy, which are tipically trained with data from a single type of endoscopy processor and have limited expert-annotated images. The investigators aim to develop and validate EndoStyle, an AI system that can generate images in the style of various processors from a single reference image. EndoStyle will be tested by showing endoscopists colonoscopy sequences with different image types to determine if they can distinguish AI-transformed images. Success would enhance AI training for diverse clinical setups.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Colon Cancer | Malignant Colon Neoplasm | CURATED_EXACT | 0.92 |
| Colon Rectal Cancer | Colon Neoplasm | PROBABILISTIC | 0.70 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| EndoStyle | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (3)
- label
- Positive control
- description
- The image shown to the participant belongs to the same colonoscopy shown in the 10 second video-sequence.
- label
- Negative control
- description
- The image shown to the participant belongs to the same colonoscopy shown in the 10 second video-sequence.
- label
- EndoStyle (intervention group)
- description
- The image shown to the participant does not belong to the 10 second colonoscopy video-sequence but has been transformed with AI to simulate the style of the video.
- interventionNames
- Device: EndoStyle
Primary outcomes (1)
- measure
- Perceptual Indistinguishability of AI-Transformed Endoscopic Images
- timeFrame
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Physicians with experience in colonoscopy.
References
Publications (0)
Data not yet available