Statistical lesion classification on brain SPECT images

Yi Ying Wang, Nan Tsing Chiu, Tiee Jian Wu, Chwin Min Weng, Wen Feng Kuo, Yung Nien Sun

Research output: Contribution to journalArticlepeer-review


Recent researches [1] have shown that individuals with more years of education have a more advanced development in Alzheimer's disease (AD) than those who with fewer years of education. In this study, two groups of fifty-eight AD patients with different education levels were examined. We utilize two statistical methods to detect the significant difference in brain region perfusion between the high and low education level patients with AD. The contextual clustering method, similar to the one for MR lesion detection in [2], is designed and applied to the 99mTc-hexamethyl propylenamine oxime (HMPAO) brain SPECT images. The other uses the SPM99 software that is commonly applied in voxel by voxel analysis of SPECT data and is popularly adopted in neuroimaging society over the past few years [3, 4]. Our finding suggests that there are significantly reductions in region perfusion in the group of high education level patients compared with the group of low education level patients. These reductions were observed in the left temporal region.

Original languageEnglish
Pages (from-to)89-96
Number of pages8
JournalJournal of Medical and Biological Engineering
Issue number2
Publication statusPublished - 2003 Jun 1

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering


Dive into the research topics of 'Statistical lesion classification on brain SPECT images'. Together they form a unique fingerprint.

Cite this