Lab Name: Medical Image Processing Lab
Introdution
Our lab focuses on developing novel data processing algorithms for neuroimaging. We are particularly interested in image registration, segmentation, and feature extraction for various medical imaging modalities. Neuroimaging data contain millions of voxels and thus robust algorithmic considerations are required to properly explore such high-dimensional data. We are witnessing exponential growth in accumulated data with advances in neuroimaging technology. Thus, the role of data post-processing will be an integral part of advanced neuroimaging research. We also have following research interests; 1) data mining for neuroimaging, 2) medical image analysis for age modeling and neurological disease, 3) medical image analysis for cancer management.
Selected Recent Publications
1. B. Park and H.Park, “Connectivity differences between adult male and female patients with attention deficit hyperactivity disorder according to resting-state fMRI”, Neural Regeneration Research, 2015.
2. B. Park, J. Seo, J. Yi, and H.Park, “Structural and functional brain connectivity of people with obesity and prediction of body mass index using connectivity”, PLoS ONE 10(11): e0141376. doi:10.1371/journal.pone.0141376, 2015.
3. S.-J. Choi*, J.-H. Kim*, J. Seo, H.-S. Kim, J.-M. Lee, and H.Park, “Parametric Response Mapping of Dynamic CT for Predicting Intrahepatic Recurrence of Hepatocellular Carcinoma after Conventional Transcatheter Arterial Chemoembolization”, European Radiology 26(1): 225-234, 2016. (* equal contribution)
4. H.Park, D. Wood, H. Hussain, C. Meyer, R. Shah, T. Johnson, T. Chenevert, and M. Piert, “Introducing Parametric PET/MR Fusion Imaging of Primary Prostate Cancer”, Journal of Nuclear Medicine 53: 546-551, 2012.
5. H.Park, P. H. Bland, and C. R. Meyer, “Construction of an Abdominal Probabilistic Atlas and its application in Segmentation", IEEE Transactions on medical imaging, 22: 483-492, 2003.