Neuronavigation using pre-operative imaging data for neurosurgical guidance is a
ubiquitous tool for the planning and resection of oncologic brain disease. These systems are …

Semi-supervised learning has a great potential in medical image segmentation tasks with a
few labeled data, but most of them only consider single-modal data. The excellent …

Intraoperative imaging, by acquiring and displaying timely information during surgery,
provides a beneficial adjunct to glioma surgery. Gliomas can be difficult to differentiate from …

Existing self-supervised medical image segmentation usually encounters the domain shift
problem (ie, the input distribution of pre-training is different from that of fine-tuning) and/or …

PURPOSE We present SlicerDMRI, an open-source software suite that enables research
using diffusion magnetic resonance imaging (dMRI), the only modality that can map the …

What is the goal of surgery for glioma? In the routine neurosurgical oncology practice there
are 2 intertwined goals: diagnostic tissue acquisition and therapeutic cytoreduction …

The human brain organoid is a miniature three-dimensional tissue culture that can simulate
the structure and function of the brain in an in vitro culture environment. Although we …

Current registration evaluations typically compute target registration error using manually
annotated datasets. As a result, the quality of landmark annotations is crucial for unbiased …

Accurate and safe neurosurgical intervention can be affected by intra-operative tissue
deformation, known as brain-shift. In this study, we propose an automatic, fast, and accurate …

Purpose The technological advancements in surgical robots compatible with magnetic
resonance imaging (MRI) have created an indispensable demand for real-time deformable …