Ovarian Cancer Identification on CT Using Deep Learning
This is not medical advice. AI-assisted translation — inaccuracies may occur. Always verify the original and consult your oncologist before taking any steps.
About the trial
Ovarian cancer remains the deadliest gynecologic malignancy, with poor survival rates largely due to late-stage diagnosis. Early detection is crucial, yet no universally accepted screening method exists. Current imaging techniques and biomarkers, such as CA-125, have limitations in specificity and sensitivity. This study aims to develop and evaluate a deep learning-based computer-aided diagnosis tool (CAT-OV), for ovarian cancer detection using CT imaging. The system integrates a Body Part Regression (BPR) model for pelvic localization and a Multiple Instance Learning (MIL) ensemble classifier for cancer prediction. The model was trained and validated using retrospective datasets from Taiwan, the United States, and a nationwide real-world cohort. Stringent preprocessing and quality control measures were implemented to enhance model accuracy. Results highlight the potential of AI-driven CT screening in improving early detection, though further validation is needed for clinical adoption.
Original English text from ClinicalTrials.gov
Who can (and can't) join
✓ Qualifies
- •Wiek co najmniej 20 lat
- •Kobiety
- •Wykonana tomografia komputerowa (zdjęcie CT)
- •Tomografia wykonana do 180 dni przed operacją jajników
✗ Disqualifies
- •Poniżej 20 lat
- •Zdjęcie CT niewystarczającej jakości lub złej orientacji
- •Zbyt mało warstw na zdjęciu (poniżej 10) lub zbyt grube warstwy (powyżej 10 mm)
- •Tomografia bez kontrastu (barwnika)
- •Artefakty metalowe na zdjęciu
- •Przypadki, w których wynik nie jest jednoznaczny
Simplified criteria — AI translation
Trial details
- Minimum age
- 20 Years
- Last updated (source)
- August 12, 2026
- Sex
- Female only
Locations (2)
Chang Gung Memorial Hospital
Taoyuan City, Taiwan
Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital
Taoyuan, Taiwan
Trial contact
Gigin Lin, MD, PhD
Contact information from ClinicalTrials.gov. Contact in English.
Share this trial
Data from ClinicalTrials.gov. AI-assisted translation, last sync: 8/13/2026.
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