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Automatic recognition and segmentation of anterior approach sciatic nerve ultrasound images based on deep learning: a single-center observational study

Automatic recognition and segmentation of anterior approach sciatic nerve ultrasound images based on deep learning

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600125641
Enrollment
Unknown
Registered
2026-05-29
Start date
2026-05-18
Completion date
Unknown
Last updated
2026-06-01

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

None

Interventions

Observational group:None

Sponsors

The Second Hospital of Lanzhou University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 70 Years

Inclusion criteria

Inclusion criteria: 1. Aged 18-70 years old; 2. Patients who are scheduled to undergo lower limb surgery and whose clinical anesthesia plan includes the planned implementation of anterior approach sciatic nerve block; 3. ASA classification is I-III; 4. Able to cooperate with ultrasound image acquisition; 5. Those who voluntarily participate in this study and sign a written informed consent form.

Exclusion criteria

Exclusion criteria: 1. ASA classification >= IV; 2. Patients with neurological or psychiatric disorders who are unable to cooperate; 3. Individuals who are allergic to ultrasound couplant; 4. Individuals with significant changes in local anatomical structures due to previous surgery/trauma in the hip, inguinal region, or proximal thigh; 5. Patients with severe sciatic nerve injury, fracture repair, or other conditions leading to significant abnormalities in the target neural structure.

Design outcomes

Primary

MeasureTime frame
Intersection over Union;Dice Coefficient;Accuracy;

Countries

China

Contacts

Public ContactHuang Shenghui

Lanzhou University Second Hospital

ery_huangshh@lzu.edu.cn+86 153 8835 2248

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jun 11, 2026