Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Structural connectome analysis using a graph-based deep model for prediction of non-imaging variables.

Frontiers in neuroscience·2026

Same author

Multimodal connectivity-based cortical segmentation with graph neural networks.

Frontiers in neuroscience·2026

Same author

Intraoperative Registration by Cross-Modal Inverse Neural Rendering.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2025

Same author

Patient-Specific Real-Time Segmentation in Trackerless Brain Ultrasound.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2025

Same author

Mapping brain tumor microstructure: A multimodal study of diffusion MRI, intraoperative fluorescence, and neuropathology in navigated biopsies.

NeuroImage. Clinical·2025

Same author

Acoustic emissions dose and spatial control of blood-brain barrier opening with focused ultrasound.

Device·2025

Same journal

Comparative Evaluation of Pretrained Large Language Models for Suicide Risk Prediction from Clinical Notes in U.S. Veterans.

medRxiv : the preprint server for health sciences·2026

Same journal

Nocturnal Respiratory Rate and Variability Predict Long-term Mortality in Stable Outpatients with Cardiovascular Disease.

medRxiv : the preprint server for health sciences·2026

Same journal

MOSAIC: Methylation-Oriented Site Analysis and Information Classifier for Robust Epigenomic Classification of Acute Leukemia in Clinical Cohorts with Variable Tumor Purity.

medRxiv : the preprint server for health sciences·2026

Same journal

Risk beliefs, intensive digital information and demand for a new preventative health product in public clinics: Evidence from an experiment in Zimbabwe.

medRxiv : the preprint server for health sciences·2026

Same journal

Development of an automated, imaging-based preoperative screening model for early identification of malnutrition in an abdominal surgery cohort.

medRxiv : the preprint server for health sciences·2026

Same journal

A Pilot Project Leveraging Large Language Models for Automated Screening and Variable Extraction in Observational Studies.

medRxiv : the preprint server for health sciences·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 15, 2025

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

Published on: August 12, 2019

ReMIND: The Brain Resection Multimodal Imaging Database.

Parikshit Juvekar¹, Reuben Dorent¹, Fryderyk Kögl^1,2

¹Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Medrxiv : the Preprint Server for Health Sciences

|September 25, 2023

Summary

This summary is machine-generated.

This study introduces the largest public database of brain tumor imaging, combining MRI and intraoperative ultrasound (iUS) data. This resource aims to advance AI-driven image analysis and improve neurosurgical techniques for brain tumor resection.

More Related Videos

Comprehensive Autopsy Program for Individuals with Multiple Sclerosis

Comprehensive Autopsy Program for Individuals with Multiple Sclerosis

Published on: July 19, 2019

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Published on: September 25, 2019

Related Experiment Videos

Last Updated: Jul 15, 2025

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

Published on: August 12, 2019

Comprehensive Autopsy Program for Individuals with Multiple Sclerosis

Comprehensive Autopsy Program for Individuals with Multiple Sclerosis

Published on: July 19, 2019

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Published on: September 25, 2019

Area of Science:

Neurosurgery
Medical Imaging
Artificial Intelligence

Background:

Maximal safe surgical resection is the standard for brain tumors, but brain shift and difficulty distinguishing tumors from healthy tissue complicate procedures.
Neuronavigation systems lose accuracy due to brain shift during surgery.
Intraoperative ultrasound (iUS) and intraoperative MRI (iMRI) aid visualization, but iUS has lower tissue contrast than iMRI.

Approach:

Developed the largest publicly available database of surgically treated brain tumors.
Collected multimodal imaging data including preoperative MRI, 3D iUS, and iMRI.
Included 356 segmentations from 114 consecutive patients at a single institution.

Key Points:

The database contains data from 92 gliomas, 11 metastases, and 11 other brain tumors.
Features 369 preoperative MRI series, 320 3D iUS series, and 301 iMRI series.
Provides 356 segmentations to support image analysis research.

Conclusions:

This comprehensive database is expected to significantly aid research in brain shift correction and medical image analysis.
It will also support neurosurgical training, particularly in interpreting intraoperative ultrasound and MRI data.
Facilitates the development and validation of AI algorithms for brain tumor imaging.