Artificial Intelligence (AI) in Nuclear Medicine

The field of nuclear medicine harmonises technologies in diagnostics and therapeutics through the use of radiopharmaceuticals. The quantification of radioactivity detected from and delivered to a patient’s body and/or tumours in the patient requires highly precise modelling and calculations, much of which can be time consuming and computationally demanding. The field of nuclear medicine employs a myriad of computational models and algorithms in reconstruction images from Positron Emission Tomography (PET) scans and also in the planning for dosimetry in radionuclide therapeutic procedures. Artificial Intelligence (AI) supplements these computational algorithms and can reduce processing time. Doctors and allied health professionals within DNMMI participates in both imaging-related and non-imaging related AI research as part of overall research efforts under the Division of Radiological Sciences. We have also curate rich clinical and imaging databases pertaining to radionuclide theranostics and PET imaging.

Contact: 

Please contact Dr Gideon Ooi Su Kai, email:  gideon.ooi.s.k@singhealth.com.sg for more information.

Publications:

1. Chen, Z., Zhou, Y., Tran, A., Zhao, J., Wan, L., Ooi, G. S. K., ... & Fu, H. (2023, October). Medical phrase grounding with region-phrase context contrastive alignment. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 371-381). Cham: Springer Nature Switzerland.

2. Qi TH, Hian OH, Kumaran AM, Tan TJ, Cong TRY, Su-Xin GL, Lim EH, Ng R, Yeo MCR, Tching FLLW, Zewen Z, Hui CYS, Xin WR, Ooi SKG, Leong LCH, Tan SM, Preetha M, Sim Y, Tan VKM, Yeong J, Yong WF, Cai Y, Nei WL; JBCR; Ai3. Multi-center evaluation of artificial intelligent imaging and clinical models for predicting neoadjuvant chemotherapy response in breast cancer. Breast Cancer Res Treat. 2022 May;193(1):121-138. doi: 10.1007/s10549-022-06521-7. Epub 2022 Mar 9. PMID: 35262831.

3. Ooi GSK, Liew C, Ting DSW, Lim TCC. Artificial Intelligence: A Singapore Response. Ann Acad Med Singap. 2020 Apr;49(4):256-258. PMID: 32296809. 

4. Ooi SKG, Makmur A, Soon AYQ, Fook-Chong S, Liew C, Sia SY, Ting YH, Lim CY. Attitudes toward artificial intelligence in radiology with learner needs assessment within radiology residency programmes: a national multi-programme survey. Singapore Med J. 2021 Mar;62(3):126-134. doi: 10.11622/smedj.2019141. Epub 2019 Nov 4. PMID: 31680181; PMCID: PMC8027147.