Advanced 3D imaging techniques and image segmentation and classification methods can transform biomedical research by offering insights into the human brain cytoarchitecture under pathological conditions. We propose a comprehensive pipeline for 3D im...
Three-dimensional (3D) ultrasound imaging is now established across a wide range of clinical applications, offering real-time volumetric visualisation of anatomical structures while remaining low-cost, portable, and non-ionising. This topical review ...
Computer assisted surgery (Abingdon, England)
Oct 31, 2025
PURPOSE: Couinaud's liver segment classification has been widely adopted for liver surgery planning, yet its rigid anatomical boundaries often fail to align precisely with individual patient anatomy. This study proposes a novel patient-specific liver...
LigPCDS (Ligand Point Cloud Data Set) is the first dataset of chemically labeled 3D point clouds of protein ligands. 3D images and structures of ligands were derived from X-ray protein crystallography experimental datasets deposited at the Protein Da...
Functional magnetic resonance imaging (fMRI) is crucial for identifying neurological disorder biomarkers, but current deep learning methods face some limitations. Template-dependent methods reliant on fixed brain atlases lack inter-subject specificit...
PURPOSE: To apply quantitative imaging analysis for noninvasive classification of the most frequent subtypes of Non-Hodgkin Lymphoma (NHL) as a basis for a clinical imaging genomic model to support therapeutic monitoring and clinical decision making.
To improve the precision of medical image segmentation for enhanced clinical diagnosis and treatment, this study focuses on overcoming the limitations of existing models in capturing multi-scale information under resolution constraints while maintain...
Multi-center collaborations are crucial in developing robust and generalizable machine learning models in medical imaging. Traditional methods, such as centralized data sharing or federated learning (FL), face challenges, including privacy issues, co...
To quantitatively measure the volume of white matter hyperintensities (WMHs) in different parts of the brain in patients with different types of cognitive function and analyze the relationship between WMH volume and cognitive function to obtain a thr...
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