ArticleHuman brain mapping2019
Automatic localization of the subthalamic nucleus on patient-specific clinical MRI by incorporating 7 T MRI and machine learning: Application in deep brain stimulation.
Article in Human brain mapping, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Artificial Intelligence for STN-DBS Surgical Planning in Parkinson's Disease: A Multicenter Study Comparing Conventional Targeting Versus Supervised Statistical Machine Learning.Brain sciences · 2026Article
- A review of applications of automated ventricular parcellation from magnetic resonance imaging of the brain.Frontiers in neurology · 2025Review
- Automated segmentation of midbrain nuclei using deep learning and multisequence MRI: A longitudinal study on iron accumulation with age.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Use of a Commercial 7-T MRI Scanner for Clinical Brain Imaging: Indications, Protocols, Challenges, and Solutions-A Single-Center Experience.AJR. American journal of roentgenology · 2023Article
- Machine learning for adaptive deep brain stimulation in Parkinson's disease: closing the loop.Journal of neurology · 2023Review
- Deep Learning Segmentation of the Nucleus Basalis of Meynert on 3T MRI.AJNR. American journal of neuroradiology · 2023Article
- Variations in Determining Actual Orientations of Segmented Deep Brain Stimulation Leads Using the DiODe Algorithm: A Retrospective Study Across Different Lead Designs and Medical Institutions.Stereotactic and functional neurosurgery · 2023Article
- Quantifying the Variability Associated with Postoperative Localization of Deep Brain Stimulation Electrodes.Stereotactic and functional neurosurgery · 2023Article
- High-resolution atlasing and segmentation of the subcortex: Review and perspective on challenges and opportunities created by machine learning.NeuroImage · 2022Review
- Advances in DBS Technology and Novel Applications: Focus on Movement Disorders.Current neurology and neuroscience reports · 2022Review
- Combining simple interactivity and machine learning: a separable deep learning approach to subthalamic nucleus localization and segmentation in MRI for deep brain stimulation surgical planning.Journal of medical imaging (Bellingham, Wash.) · 2022Article
- Lead location as a determinant of motor benefit in subthalamic nucleus deep brain stimulation for Parkinson's disease.Frontiers in neuroscience · 2022Article
- Automated Segmentation of Midbrain Structures in High-Resolution Susceptibility Maps Based on Convolutional Neural Network and Transfer Learning.Frontiers in neuroscience · 2022Article
- Deep-learning based fully automatic segmentation of the globus pallidus interna and externa using ultra-high 7 Tesla MRI.Human brain mapping · 2021Article
- Computational Complexity Reduction of Neural Networks of Brain Tumor Image Segmentation by Introducing Fermi-Dirac Correction Functions.Entropy (Basel, Switzerland) · 2021Article
- StimVision v2: Examples and Applications in Subthalamic Deep Brain Stimulation for Parkinson's Disease.Neuromodulation : journal of the International Neuromodulation Society · 2021Article
- New Frontiers for Deep Brain Stimulation: Directionality, Sensing Technologies, Remote Programming, Robotic Stereotactic Assistance, Asleep Procedures, and Connectomics.Frontiers in neurology · 2021Review
- Artificial intelligence for brain diseases: A systematic review.APL bioengineering · 2020Review
- Machine Learning's Application in Deep Brain Stimulation for Parkinson's Disease: A Review.Brain sciences · 2020Review
- Deep Cerebellar Nuclei Segmentation via Semi-Supervised Deep Context-Aware Learning from 7T Diffusion MRI.IEEE access : practical innovations, open solutions · 2020Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has shown clinical potential for relieving the motor symptoms of advanced Parkinson's disease. While accurate localization of the STN is critical for consistent across-patients effective DBS, clear visualization of the STN under standard clinical MR protocols is still challenging. Therefore, intraoperative microelectrode recordings (MER) are incorporated to accurately localize the STN. However, MER require significant neurosurgical expertise and lengthen the surgery time. Recent advances in 7 T MR technology facilitate the ability to clearly visualize the STN. The vast majority of centers, however, still do not have 7 T MRI systems, and fewer have the ability to collect and analyze the data. This work introduces an automatic STN localization framework based on standard clinical MRIs without additional cost in the current DBS planning protocol. Our approach benefits from a large database of 7 T MRI and its clinical MRI pairs. We first model in the 7 T database, using efficient machine learning algorithms, the spatial and geometric dependency between the STN and its adjacent structures (predictors). Given a standard clinical MRI, our method automatically computes the predictors and uses the learned information to predict the patient-specific STN. We validate our proposed method on clinical T
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.