2021 Post-doctoral Non-clinical Fellowship
Integrated AI tools for the prediction of tumour invasion using brain MRI scans
Glioblastoma is a highly aggressive type of brain cancer that poses significant difficulties in its treatment. The current standard of care involves surgical removal of the tumour followed by radiation therapy. However, one of the major challenges is the frequent recurrence of tumours in areas adjacent to the treated region, indicating the presence of undetectable tumours using conventional diagnostic methods.
Artificial intelligence (AI) holds great promise in addressing this issue by enabling the effective detection of tumour regions, thus facilitating more targeted and effective surgical procedures and radiation therapy. However, the development of robust AI models often requires access to large volumes of clinical data, which can be challenging to obtain in practical healthcare settings. Moreover, for the sake of patient safety, it is crucial for clinicians to have a clear understanding of the decision-making process of AI models, which is often lacking in black-box AI models.
To overcome these challenges, this project aims to develop novel AI techniques specifically designed to predict tumour invasion based on brain MRI scans. The goal is to create an AI solution for real-world healthcare that is both reliable and trustworthy. The proposed AI model could be seamlessly integrated into existing clinical systems, allowing for practical implementation within healthcare facilities. Furthermore, its performance and accuracy will be rigorously evaluated using the data collected from clinical trials.
The integration of AI tools has the potential to significantly enhance the ability of clinicians to identify hidden tumour regions. By providing precise information about tumour invasion, the AI solution can help guide surgical interventions and radiation therapy, leading to improved patient outcomes. Additionally, once the AI solution is validated, it can be scaled and deployed across multiple healthcare centres, offering a cost-effective approach to benefit the healthcare system and our society at large.
Publications
Multi-modal learning for predicting the genotype of glioma
IEEE Transactions on Medical Imaging
2023
Structural connectome quantifies tumour invasion and predicts survival in glioblastoma patients
Brain 146(4), pp.1714-1727
2023
Prognostic significance of MRI-based late-course tumor volume in locoregionally advanced nasopharyngeal carcinoma
Radiation Oncology, 17(1), 111.4
2022
MIR99AHG inhibits EMT in pulmonary fibrosis via the miR-136-5p/USP4/ACE2
Journal of Translational Medicine, 20(1), 1-18.5
2022
Cerebrovascular risk factors impact brain phenotypes and cognitive function in healthy population
medRxiv. doi: https://doi.org/10.1101/2022.03.29.22273047 (Preprint)
2022
Integrating Histomics and Genomics for Multi-task Prediction of Diffuse Glioma
International Conference on Medical Image Computing and Computer Assisted Intervention 2023
2023
Geometric Enhancement of Magnetic Resonance Imaging for Accurate Skull-Stripping Segmentation
International Conference on Medical Image Computing and Computer Assisted Intervention 2023
2023
MM-LDiff: Muti-Modalities Conditioned Latent Diffusion Model for Missing MRI Sequence Synthesis
International Conference on Medical Image Computing and Computer Assisted Intervention 2023
2023
UCD-DM: A Unified Conditional Diffusion Model Enhanced by Disentangled Representation Learning for Multi-Contrast Brain MRI Super-Resolution
International Conference on Medical Image Computing and Computer Assisted Intervention 2023
2023
Predicting conversion of mild cognitive impairment to Alzheimer's disease by modelling healthy ageing trajectories
2023 IEEE 20th International Symposium on Biomedical Imaging
2023
Collaborative learning of images and geometrics for predicting isocitrate dehydrogenase status of glioma
2023 IEEE 20th International Symposium on Biomedical Imaging
2023
Mutual Contrastive Learning to Disentangle Whole Slide Image Representations for Glioma Grading
2022 British Machine Vision Virtual Conference
2022
The anisotropic component of the diffusion tensor (dti-q) is correlated to overall survival in glioblastoma
British Neuro-Oncology Society 2022
2022
Predicting isocitrate dehydrogenase mutation status using contrastive learning and graph neural networks
Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting
2022
Incorporating Histological Grading for Brain Tumor Segmentation
Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting
2022