ArticleIEEE transactions on medical imaging2020
Evaluation of MRI to Ultrasound Registration Methods for Brain Shift Correction: The CuRIOUS2018 Challenge.
Article in IEEE transactions on medical imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Advances in Preoperative and Intraoperative Technologies for Safe Resection of Gliomas in Cognitive Regions.Cancers · 2025Review
- Optimizing registration uncertainty visualization to support intraoperative decision-making during brain tumor resection.International journal of computer assisted radiology and surgery · 2025Article
- Spatial variations and precise location of substantia nigra hyperechogenicity in Parkinson's disease using TCS-MR fusion imaging.NPJ Parkinson's disease · 2025Article
- Towards automatic US-MR fetal brain image registration with learning-based methods.NeuroImage · 2025Article
- Contrast-enhanced ultrasound can differentiate the level of glioma infiltration and correlate it with biological behavior: a study based on local pathology.Journal of ultrasound · 2025Article
- Role of Virtual iMRI in Glioblastoma Surgery: Advantages, Limitations, and Correlation with iCT and Brain Shift.Brain sciences · 2024Article
- BIFROST: A method for registering diverse imaging datasets of theProceedings of the National Academy of Sciences of the United States of America · 2024Article
- Sensorless End-to-End Freehand 3-D Ultrasound Reconstruction With Physics-Guided Deep Learning.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2024Article
- Mutual Information Guided Diffusion for Zero-Shot Cross-Modality Medical Image Translation.IEEE transactions on medical imaging · 2024Article
- DDiagnostics (Basel, Switzerland) · 2024Article
- Enabling Navigation and Augmented Reality in the Sitting Position in Posterior Fossa Surgery Using Intraoperative Ultrasound.Cancers · 2024Article
- ReMIND: The Brain Resection Multimodal Imaging Database.Scientific data · 2024Article
- ReMIND: The Brain Resection Multimodal Imaging Database.medRxiv : the preprint server for health sciences · 2024Article
- Unsupervised deep learning registration model for multimodal brain images.Journal of applied clinical medical physics · 2023Article
- Advances in TEE-Centric Intraprocedural Multimodal Image Guidance for Congenital and Structural Heart Disease.Diagnostics (Basel, Switzerland) · 2023Review
- A hybrid deformable registration method to generate motion-compensated 3D virtual MRI for fusion with interventional real-time 3D ultrasound.International journal of computer assisted radiology and surgery · 2023Article
- [Multiresolution discrete optimization registration method of ultrasound and magnetic resonance images based on key points].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023Article
- Automatic rigid image Fusion of preoperative MR and intraoperative US acquired after craniotomy.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023Article
- Photoacoustic-MR Image Registration Based on a Co-Sparse Analysis Model to Compensate for Brain Shift.Sensors (Basel, Switzerland) · 2022Article
- Intraoperative MR Imaging during Glioma Resection.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2022Review
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16 authors.
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Abstract
In brain tumor surgery, the quality and safety of the procedure can be impacted by intra-operative tissue deformation, called brain shift. Brain shift can move the surgical targets and other vital structures such as blood vessels, thus invalidating the pre-surgical plan. Intra-operative ultrasound (iUS) is a convenient and cost-effective imaging tool to track brain shift and tumor resection. Accurate image registration techniques that update pre-surgical MRI based on iUS are crucial but challenging. The MICCAI Challenge 2018 for Correction of Brain shift with Intra-Operative UltraSound (CuRIOUS2018) provided a public platform to benchmark MRI-iUS registration algorithms on newly released clinical datasets. In this work, we present the data, setup, evaluation, and results of CuRIOUS 2018, which received 6 fully automated algorithms from leading academic and industrial research groups. All algorithms were first trained with the public RESECT database, and then ranked based on a test dataset of 10 additional cases with identical data curation and annotation protocols as the RESECT database. The article compares the results of all participating teams and discusses the insights gained from the challenge, as well as future work.
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