Highly resolved diffuse optical tomography: a systematic approach using high-pass filtering for value-preserved images

  • Pan M
  • Chen C
  • Chen L
  • et al.
10Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

Abstract

We attempt to develop a systematic scheme through adopting high-pass filtering (HPF) to well resolve value-preserved images such as medical images. Our approach is derived from the Poisson maximum a posteriori superresolution algorithm employing the HP filters, where four filters are considered such as two low-pass-filter-combination based filters, wavelet filter, and negative-oriented Laplacian HP filter. The proposed approach is incorporated into the procedure of finite-element-method (FEM)-based image reconstruction for diffuse optical tomography in the direct current domain, posterior to each iteration without altering the original FEM modeling. This approach is justified with various HPF for different cases that breast-like phantoms embedded with two or three inclusions that imitate tumors are employed to examine the resolution performances under certain extreme conditions. The proposed approach to enhancing image resolution is evaluated for all tested cases. A qualitative investigation of reconstruction performance for each case is presented. Following this, we define a set of measures on the quantitative evaluation for a range of resolutions including separation, size, contrast, and location, thereby providing a comparable evaluation to the visual quality. The most satisfactory result is obtained by using the wavelet HP filter, and it successfully justifies our proposed scheme. © 2008 Society of Photo-Optical Instrumentation Engineers.

Cite

CITATION STYLE

APA

Pan, M.-C., Chen, C.-H., Chen, L.-Y., Pan, M.-C., & Shyr, Y.-M. (2008). Highly resolved diffuse optical tomography: a systematic approach using high-pass filtering for value-preserved images. Journal of Biomedical Optics, 13(2), 024022. https://doi.org/10.1117/1.2907344

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free