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Development of key technologies in deep learning based intelligent surgical planning and implementation system for pelvic tumors

Development of key technologies in deep learning based intelligent surgical planning and implementation system for pelvic tumors

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300069221
Enrollment
Unknown
Registered
2023-03-09
Start date
2023-03-10
Completion date
Unknown
Last updated
2023-05-29

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

Conditions

bone tumour

Interventions

control group:N/A
osteotomy template group:N/A

Sponsors

Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1. Patients with bone tumors who have surgical indications and can tolerate surgical trauma; 2. No implant contraindications; 3. Patients who voluntarily signed the informed consent form and had no contraindications to CT and MRI examination; 4. Have not participated in any clinical validation within 3 months; 5. Aged 18-80 years.

Exclusion criteria

Exclusion criteria: 1. The new technology used in this experiment cannot be accepted; 2. Patients with history of metal prosthesis implantation in pelvis; 3. Patients who cannot follow up on schedule or cannot cooperate with researchers for other reasons.

Design outcomes

Primary

MeasureTime frame
osteotomy plane distance;osteotomy plane angle;—

Countries

China

Contacts

Public ContactAi Songtao

Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine

aistss1024@sjtu.edu.cn+86 180 1979 0801

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026