Summary of Merlin: a Vision Language Foundation Model For 3d Computed Tomography, by Louis Blankemeier et al.
Merlin: A Vision Language Foundation Model for 3D Computed Tomography
by Louis Blankemeier, Joseph Paul Cohen, Ashwin Kumar, Dave Van Veen, Syed Jamal Safdar Gardezi, Magdalini Paschali, Zhihong Chen, Jean-Benoit Delbrouck, Eduardo Reis, Cesar Truyts, Christian Bluethgen, Malte Engmann Kjeldskov Jensen, Sophie Ostmeier, Maya Varma, Jeya Maria Jose Valanarasu, Zhongnan Fang, Zepeng Huo, Zaid Nabulsi, Diego Ardila, Wei-Hung Weng, Edson Amaro Junior, Neera Ahuja, Jason Fries, Nigam H. Shah, Andrew Johnston, Robert D. Boutin, Andrew Wentland, Curtis P. Langlotz, Jason Hom, Sergios Gatidis, Akshay S. Chaudhari
First submitted to arxiv on: 10 Jun 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel 3D vision language model, Merlin, is introduced to alleviate the burden of interpreting computed tomography (CT) scans in radiology. By leveraging paired CT scans, electronic health record diagnosis codes, and radiology reports, Merlin is trained for various tasks including zero-shot findings classification, phenotype classification, and cross-modal retrieval. The model achieves favorable performance compared to existing task-specific baselines and requires only a single GPU for training. Data scaling laws are derived to empirically assess the training data needs for downstream task performance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new AI tool is being developed to help doctors analyze CT scans more efficiently. This tool, called Merlin, uses artificial intelligence to look at CT scans, electronic health records, and doctor’s reports to make it easier for radiologists to do their jobs. The goal is to use this technology to reduce the workload of radiologists and make healthcare more efficient. |
Keywords
» Artificial intelligence » Classification » Language model » Scaling laws » Zero shot
