End-to-End Dementia Status Prediction from Brain MRI Using Multi-task Weakly-Supervised Attention Network

@inproceedings{Lian2019EndtoEndDS,
  title={End-to-End Dementia Status Prediction from Brain MRI Using Multi-task Weakly-Supervised Attention Network},
  author={Chunfeng Lian and Mingxia Liu and Lei Wang and Dinggang Shen},
  booktitle={MICCAI},
  year={2019}
}
  • Chunfeng Lian, Mingxia Liu, +1 author Dinggang Shen
  • Published in MICCAI 2019
  • Computer Science
  • Computer-aided prediction of dementia status (e.g., clinical scores of cognitive tests) from brain MRI is of great clinical value, as it can help assess pathological stage and predict disease progression. Existing learning-based approaches typically preselect dementia-sensitive regions from the whole-brain MRI for feature extraction and prediction model construction, which might be sub-optimal due to potential heterogeneities between different steps. Also, based on anatomical prior knowledge (e… CONTINUE READING

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