In-house data adaptation to public data: Multisite MRI harmonization to predict Alzheimer's disease conversion - Park, Sunghong; Son, Sang Joon; Park, Kanghee; Nam, Yonghyun; Shin, Hyunjung (Expert Systems with Applications, 2024)
For the machine learning-based prediction of the conversion from mild cognitive impairment to Alzheimer's disease, the collection of sufficient data to train a model is required, which involves a lot of time and expense. When data is not enough, combining public and in-house data may be appropriate by applying domain adaptation that alleviates inter-site heterogeneity. Existing methods simultaneously transform in-house and public data to represent them into a common feature space, and then train a classifier using labels in public data. However, this procedure causes the time- and cost-consuming re-training of classifier whenever in-house data changes, and also inheres the risk of information loss in public data. Motivated by this, we propose a method that only transforms in-house data while preserving public data, namely one-way domain adaptation. The proposed method represents in-house data similar with public data by matching the data distribution and the connectivity between brain regions with mean vectors and covariance matrices, respectively. Then, the pre-trained classifier in public data is applied to predict AD conversion for in-house data. The experiments, which use the Australian Imaging Biomarkers and Lifestyle Study of Aging and the Open Access Series of Imaging Studies as the in-house data and the Alzheimer's Disease Neuroimaging Initiative as the public data, show the effectiveness and efficiency of the proposed method, improving prediction performance about 34.8% on average without labels in the in-house datasets.
Keywords: Alzheimers disease; Cognitive impairment; Connectivity mapping; Distribution matching; Domain adaptation; Harmonisation; Mild cognitive impairment; Multi-site; Multisite MRI harmonization; Public data; Alzheimer's disease; Connectivity mapping; Distribution matching; Domain adaptation; Mild cognitive impairment; Multisite MRI harmonization