With the advances of data-driven machine learning research, a wide variety of prediction
problems have been tackled. It has become critical to explore how machine learning and …

State-of-the-art deep learning models often fail to generalize in the presence of distribution
shifts between training (source) data and test (target) data. Domain adaptation methods are …

Accurate and consistent predictions of echocardiography parameters are important for
cardiovascular diagnosis and treatment. In particular, segmentations of the left ventricle can …

The deployment of Graph Neural Networks (GNNs) within Machine Learning as a Service
(MLaaS) has opened up new attack surfaces and an escalation in security concerns …

Commonly-used tools for cortical reconstruction and parcellation, such as FreeSurfer, are
central to brain surface analysis but require extensive computation times. This paper …

DeepLift is a special Layer-wise Relevance Propagation (LRP) algorithm that assigns
importance to features by evaluating the impact of small perturbations in input features on …

Medical Image Analysis (MedIA) has become indispensable in modern healthcare,
enhancing clinical diagnostics and personalized treatment. Despite the remarkable …

In order to understand the organizational structures of healthy cerebral cortex and the
abnormalities in neurological and psychiatric diseases, it is significant to parcellate the …

Reconstructing and segmenting cortical surfaces from MRI is essential to a wide range of
brain analyses. However, most approaches follow a multi-step slow process, such as a …

Integrating frameworks of Fermi normalization and fast data density functional transform
(fDDFT), we established a new global convolutional self-action module to reduce the …