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Surgical-DINO: adapter learning of foundation models for depth estimation in endoscopic surgery.

Beilei CuiMobarakol IslamLong BaiHongliang Ren
Published in: International journal of computer assisted radiology and surgery (2024)
Surgical-DINO shed some light on the successful adaptation of the foundation models into the surgical domain for depth estimation. There is clear evidence in the results that zero-shot prediction on pre-trained weights in computer vision datasets or naive fine-tuning is not sufficient to use the foundation model in the surgical domain directly.
Keyphrases
  • minimally invasive
  • optical coherence tomography
  • deep learning
  • coronary artery bypass