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Evaluation of MRI to ultrasound registration methods for brain shift correction: The CuRIOUS2018 Challenge

arXiv 1904.10535 ↗First posted 23 Apr 2019eess.IVcited by 16

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Abstract (arXiv)

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 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.

Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 Apr 2019.

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Citing papers per year: 2021: 2; 2022: 2; 2023: 5; 2024: 1; 2025: 1; 2026: 5.

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  1. 2021Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learningcited by 125
  2. 2021The Brain Tumor Sequence Registration (BraTS-Reg) Challenge: Establishing Correspondence Between Pre-Operative and Follow-up MRI Scans of Diffuse Glioma Patientscited by 32
  3. 2024Modality-Agnostic Structural Image Representation Learning for Deformable Multi-Modality Medical Image Registrationcited by 17
  4. 2022Global Multi-modal 2D/3D Registration via Local Descriptors Learningcited by 13
  5. 2023A Survey of Emerging Applications of Diffusion Probabilistic Models in MRIcited by 9
  6. 2023Zero-shot-Learning Cross-Modality Data Translation Through Mutual Information Guided Stochastic Diffusioncited by 6
  7. 2023Towards multi-modal anatomical landmark detection for ultrasound-guided brain tumor resection with contrastive learningcited by 4
  8. 2023FocalErrorNet: Uncertainty-aware focal modulation network for inter-modal registration error estimation in ultrasound-guided neurosurgerycited by 3
  9. 2023Dense Error Map Estimation for MRI-Ultrasound Registration in Brain Tumor Surgery Using Swin UNETRcited by 2
  10. 2026MedRCube: A Multidimensional Framework for Fine-Grained and In-Depth Evaluation of MLLMs in Medical Imagingcited by 2
  11. 2026A Systematic Benchmark of Intraoperative Ultrasound-to-MR Synthesis for Brain Tumour Surgerycited by 2
  12. 2022Are metaheuristics worth it? A computational comparison between nature-inspired and deterministic techniques on black-box optimization problemscited by 0
4 more
  1. 2025OncoReg: Medical Image Registration for Oncological Challengescited by 0
  2. 2026Data-driven registration and modeling of brain deformation for image-guided neurosurgerycited by 0
  3. 2026Deep learning based Non-Rigid Volume-to-Surface Registration for Brain Shift compensation Using Point Cloudcited by 0
  4. 2026What neurosurgeons need to see: synthetic intra-operative MRI from ultrasound for brain-shift compensation in brain tumour surgerycited by 0