Nonnegative Mixed-Norm Preconditioning for Microscopy Image Segmentation
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
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Differential interference contrast (DIC) microscopy is a powerful visualization tool used to study live biological cells. Its use, however, has been limited to qualitative observations. The inherent nonlinear relationship between the object properties and the image intensity makes quantitative analysis difficult. Toward quantitatively measuring optical properties of objects from DIC images, we develop a method to reconstruct the specimen's optical properties over a three-dimensional (3-D) volume. The method is a nonlinear optimization which uses hierarchical representations of the specimen and data. As a necessary tool, we have developed and validated a computational model for the DIC image formation process. We test our algorithm by reconstructing the optical properties of known specimens.