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by rozain - opened
README.md
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# For reference on dataset card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
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# Doc / guide: https://huggingface.co/docs/hub/datasets-cards
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{}
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<div align="center">
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## Dataset Summary
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MedSPOT is a benchmark for evaluating Multimodal Large Language Models (MLLMs) on GUI grounding tasks in medical imaging software. It evaluates models on their ability to localize and interact with UI elements across 10 medical imaging applications including 3DSlicer, DICOMscope, Weasis, MITK, and others.
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# For reference on dataset card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
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# Doc / guide: https://huggingface.co/docs/hub/datasets-cards
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{}
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<div align="center">
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<img src="https://user-images.githubusercontent.com/74038190/212284115-f47cd8ff-2ffb-4b04-b5bf-4d1c14c0247f.gif"
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width="100%" />
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</div>
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<table>
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<tr>
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<td width="25%" align="center" valign="middle">
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<img src="https://raw.githubusercontent.com/Tajamul21/MedSPOT/main/Images/medspot2.jpeg" width="100%" style="border-radius: 12px;" />
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</td>
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<td width="55%" align="center">
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<h1 align="center">🧠 MedSPOT</h1>
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<h3 align="center"><i>A Workflow-Aware Sequential Grounding Benchmark for Clinical GUI</i></h3>
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<h3 align="center">
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<a href="https://github.com/RozainMalik">Rozain Shakeel</a><sup>1</sup>,
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<a href="https://www.linkedin.com/in/rxhman/">Abdul Rahman Mohammad Ali</a><sup>2</sup>,
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<a href="https://www.linkedin.com/in/muneeb-ahmad-ganie">Muneeb Mushtaq</a><sup>1</sup>,
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<a href="https://rozainmalik.github.io/MedSPOT_web/">Tausifa Jan Saleem</a><sup>3</sup>,
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<b><a href="https://www.tajamulashraf.com/">Tajamul Ashraf</a><sup>1,4*</sup></b>
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</h3>
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<h4 align="center">
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<sup>*</sup> Corresponding author
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</h4>
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<h3 align="center">
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<sup>1</sup> Gaash Research Lab, National Institute of Technology Srinagar, India<br>
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<sup>2</sup> e& Group, UAE<br>
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<sup>3</sup> Mohammad Bin Zayed University of Artificial Intelligence (MBZUAI), UAE<br>
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<sup>4</sup> King Abdullah University of Science and Technology (KAUST), Saudi Arabia
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</h3>
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</td>
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</tr>
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</table>
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## Dataset Summary
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MedSPOT is a benchmark for evaluating Multimodal Large Language Models (MLLMs) on GUI grounding tasks in medical imaging software. It evaluates models on their ability to localize and interact with UI elements across 10 medical imaging applications including 3DSlicer, DICOMscope, Weasis, MITK, and others.
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