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I am primarily interested in developing novel image registration techniques that enable 3D US images, acquired during an intervention, to be used to register pre-treatment MR/CT images to the patient during an intervention. US imaging is well suited to this purpose, as it is safe, non-invasive, inexpensive, portable, widely available, and extremely versatile. Importantly, it also allows dense information on organ deformation to be obtained, compensation of which is essential for accurate guidance during some interventions. Essentially, this problem is a “multimodal” image registration task, where the aim is to align the US images with the MR/CT images. However, because the characteristics of US images are so different to MR or CT images (in terms of grey-level intensity characteristics and artefacts), in general, this is a challenging problem for which general-purpose, automatic solutions do not currently exist.
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Zhe Min,Fernando J. Bianco,Qianye Yang,Wen Yan,Ziyi Shen, David Cohen, Rachael Rodell,Dean C. Barratt,Yipeng Hu
CAAI Transactions on Intelligence Technology (2024)
MACHINE LEARNING IN MEDICAL IMAGING, MLMI 2023, PT I (2024): 277-288
CoRR (2024)
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International Journal of Computer Assisted Radiology and Surgerypp.1-10, (2024)
MEDICAL IMAGE ANALYSIS (2024): 103030-103030
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