Unified Supervision For Vision-Language Modeling in 3D Computed Tomography

Documenti analoghi

• VIS-MAE: An Efficient Self-supervised Learning Approach on Medical Image Segmentation and Classification
  di: Liu, Zelong, et al.
  Pubblicazione: (2024)
• A review of self‐supervised, generative, and few‐shot deep learning methods for data‐limited magnetic resonance imaging segmentation
  di: Zelong Liu, et al.
  Pubblicazione: (2024)
• MRAnnotator: multi-Anatomy and many-Sequence MRI segmentation of 44 structures
  di: Zhou, Alexander, et al.
  Pubblicazione: (2024)
• G-SHARP: Gaussian Surgical Hardware Accelerated Real-time Pipeline
  di: Nath, Vishwesh, et al.
  Pubblicazione: (2025)
• No Tokens Wasted: Leveraging Long Context in Biomedical Vision-Language Models
  di: Sun, Min Woo, et al.
  Pubblicazione: (2025)