Tensor regularized total variation for denoising of third harmonic generation images of brain tumors.

ABSTRACT: Third harmonic generation (THG) microscopy shows great potential for instant pathology of brain tissue during surgery. However, the rich morphologies contained and the noise associated makes image restoration, necessary for quantification of the THG images, challenging. Anisotropic diffusion filtering (ADF) has been recently applied to restore THG images of normal brain, but ADF is hard-to-code, time-consuming and only reconstructs salient edges. This work overcomes these drawbacks by expressing ADF as a tensor regularized total variation model, which uses the Huber penalty and the L₁ norm for tensor regularization and fidelity measurement, respectively. The diffusion tensor is constructed from the structure tensor of ADF yet the tensor decomposition is performed only in the non

SUBMITTER: Zhang Z 

PROVIDER: S-EPMC7065612 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature