A hybrid self-supervised teacher–student model for predicting neurovascular bundle preservation in prostatectomy videos
Incorporating representation learning through self-distillation, classification, and reconstruction provides complementary signals that enhance the prediction of NVB preservation. Our Hybrid T-S model can assist surgeons in real decision-making and improve patient recovery.
Authors
- Satoshi Ando (ORCID: https://orcid.org/0000-0001-9964-1219)
- Hiroshi Kawahira
- Yukihiro Nomura (ORCID: https://orcid.org/0000-0001-6471-9936)
- Huitao Wang (ORCID: https://orcid.org/0009-0008-6299-5855)
- Hayato Hoshina
- Diego Andrés del Aguila Moraga
- Toshiya Nakaguchi
Institutions
- Jichi Medical University (JP)
- Chiba University (JP)
Publication Details
- Journal
- International Journal of Computer Assisted Radiology and Surgery
- Published
- 2026-02-12
- DOI
- https://doi.org/10.1007/s11548-025-03544-5
- Primary Topic
- Prostate Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00