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RESEARCH PRODUCT
MedAI: Transparency in Medical Image Segmentation
Steven Alexander HicksPål HalvorsenKlas PettersenThomas De LangeBjørn-jostein SingstadMorten GoodwinSachin GaurMichael RieglerDebesh JhaSravanthi ParasaVajira Thambawitasubject
Computer sciencebusiness.industryTransparency (graphic)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONSegmentationImage segmentationArtificial intelligenceMachine learningcomputer.software_genrebusinesscomputerField (computer science)description
MedAI: Transparency in Medical Image Segmentation is a challenge held for the first time at the Nordic AI Meet that focuses on medical image segmentation and transparency in machine learning (ML)-based systems. We propose three tasks to meet specific gastrointestinal image segmentation challenges collected from experts within the field, including two separate segmentation scenarios and one scenario on transparent ML systems. The latter emphasizes the need for explainable and interpretable ML algorithms. We provide a development dataset for the participants to train their ML models, tested on a concealed test dataset.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2021-11-01 | Nordic Machine Intelligence |