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VADH 2025 : First Workshop on Vision-Based AI for Digital Health: From Pixels to Practice | |||||||||||||||
Link: https://sites.google.com/view/vadh25/home | |||||||||||||||
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Call For Papers | |||||||||||||||
We invite paper submissions with topics include, but not limited to:
- Vision LLM for Healthcare * Improving diagnostic accuracy in clinical settings * Improving treatment planning in clinical settings * Interpreting medical images * Generating detailed clinical reports - Medical Image Analysis and Diagnostics * Detecting abnormalities * Improving diagnostic precision * Supporting treatment planning - Real-Time 3D Reconstruction for Medical Endoscopy * Challenges in Endoscopic 3D Reconstruction * Methodological Spectrum * Adaptations for Endoscope Types * Benchmarking & Datasets - Applications in Digital Health * Identifying cancerous lesions at early stages * Wound monitoring through sequential image analysis to track healing progress * Gait analysis via video-based methods to assess patient mobility * Remote patient monitoring using live video streams to continuously track vital signs and patient behaviors Paper formatting: Papers must be a minimum of 4 pages and may not exceed 8 pages, including all figures and tables, formatted in the official ICCV style. Additional pages are permitted only for references. Please download the ICCV 2025 Author Kit (https://media.eventhosts.cc/Conferences/ICCV2025/ICCV2025-Author-Kit-Feb.zip) for detailed formatting instructions. Please follow the ICCV 2025 Author Guidelines (https://iccv.thecvf.com/Conferences/2025/AuthorGuidelines) and submit your paper through the VADH 2025 submission portal on Openreview (https://openreview.net/group?id=thecvf.com/ICCV/2025/Workshop/VADH). Accepted papers will be published in the ICCV 2025 Workshop Proceedings following the ICCV 2025 publication guidelines. |
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