Biomedical imaging

The basic medical science research and clinical diagnosis and treatment
have strongly benefited from the development of various noninvasive
biomedical imaging techniques, e.g. magnetic resonance imaging (MRI) and
computed tomography (CT). The mathematical tools provide many different
ways to analyze these valuable images. In this talk, we will give examples
of morphology and connectome study of human brains, the shape analysis of
ciliary muscle of human eyes, and the estimate of oxygen transport in
tissue transfer.

Measured bioresponses are often characterized by
an intrinsic high frequency and strong persistent correlations
inhibiting statistical modeling by the traditional techniques.
The talk overviews two novel wavelet-based techniques
for modeling such challenging data.

Wavelet domains provide natural modeling
environments for data that scale, as well as for data
consisting of continuous n-dimensional functions.
We briefly discuss technicalities and describe in detail
two applications.