Glioma represents a dominant primary intracranial malignancy in the central nervous
system. Artificial intelligence that mainly includes machine learning, and deep learning …

Raman spectroscopy, as a label-free optical technology, has widely applied in tumor
diagnosis. Relying on the different Raman technologies, conventional diagnostic methods …

Molecular classification has transformed the management of brain tumors by enabling more
accurate prognostication and personalized treatment. However, timely molecular diagnostic …

Molecular imaging is one of the pillars of precision surgery. Its applications range from early
diagnostics to therapy planning, execution, and the accurate assessment of outcomes. In …

Glioblastomas (GBM) are the most common and aggressive tumors of the central nervous
system. Rapid tumor growth and diffuse infiltration into healthy brain tissue, along with high …

Brain disorders such as brain tumors and neurodegenerative diseases (NDs) are
accompanied by chemical alterations in the tissues. Early diagnosis of these diseases will …

Learning high-quality, self-supervised, visual representations is essential to advance the
role of computer vision in biomedical microscopy and clinical medicine. Previous work has …

Core-needle biopsy (CNB) plays a vital role in the initial diagnosis of breast cancer.
However, the complex tissue processing and global shortage of pathologists have hindered …

Accurate intraoperative diagnosis is essential for providing safe and effective care during
brain tumor surgery. Our standard-of-care diagnostic methods are time, resource, and labor …

Determining the presence of tumor in biopsies and the decision-making during resections is
often dependent on intraoperative rapid frozen-section histopathology. Recently, stimulated …