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Applying deep learning methods to solve several problems in CBCT-based ART

Applying deep learning methods to solve several problems in CBCT-based ART

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300074194
Enrollment
Unknown
Registered
2023-08-01
Start date
2023-08-01
Completion date
Unknown
Last updated
2023-08-07

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

Conditions

tumor

Interventions

Comparative observation group:Comparative observation

Sponsors

West China Hospital of Sichuan University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
1 Years to 100 Years

Inclusion criteria

Inclusion criteria: The following five criteria must be met simultaneously: (1)From January 2015 to December 2022, the patient received the treatment of radiotherapy for chest tumors in West China Hospital of Sichuan University; (2)Receiving at least two courses of radiotherapy, namely the presence of at least two treatment plans; (3)Received image-guided radiotherapy; (4)There are at least 5 CBCT sequences for each session, that is, at least 5 treatments for each session; (5)The Varian edge electron linear accelerator was used for treatment.

Exclusion criteria

Exclusion criteria: Those that did not meet the above inclusion criteria were excluded.

Design outcomes

Primary

MeasureTime frame
image quality;dose;—

Countries

China

Contacts

Public Contactli xia

West China Hospital of Sichuan University

lixia_rt_wch@scu.edu.cn+86 182 0811 9069

Outcome results

None listed

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