Dzena Hidović-Rowe | PubMed Health

PubMed2006

Markov models of integrating spheres for hyperspectral imaging.

Theoretical models of the signal detected by a CCD camera during hyperspectral imaging with an integrating sphere are derived using Markov chains with absorbing states. The models provide analytical expressions that describe the real reflectance of the sample as a function of the detected signal at each pixel of the image. Validation of the models was done by using reflectance standards and tissue phantoms. The models provide accurate analytical solutions for samples and spheres that are near-Lambertian reflectors.

Journal Article↗

PubMed2005

Modelling and validation of spectral reflectance for the colon.

The spectral reflectance of the colon is known to be affected by malignant and pre-malignant changes in the tissue. As part of long-term research on the derivation of diagnostically important parameters characterizing colon histology, we have investigated the effects of the normal histological variability on the remitted spectra. This paper presents a detailed optical model of the normal colon comprising mucosa, submucosa and the smooth muscle layer. Each layer is characterized by five variable histological parameters: the volume fraction of blood, the haemoglobin saturation, the size of the scattering particles, including collagen, the volume fraction of the scattering particles and the layer thickness, and three optical parameters: the anisotropy factor, the refractive index of the medium and the refractive index of the scattering particles. The paper specifies the parameter ranges corresponding to normal colon tissue, including some previously unpublished ones. Diffuse reflectance spectra were modelled using the Monte Carlo method. Validation of the model-generated spectra against measured spectra demonstrated that good correspondence was achieved between the two. The analysis of the effect of the individual histological parameters on the behaviour of the spectra has shown that the spectral variability originates mainly from changes in the mucosa. However, the submucosa and the muscle layer must be included in the model as they have a significant constant effect on the spectral reflectance above 600 nm. The nature of variations in the spectra also suggests that it may be possible to carry out model inversion and to recover parameters characterizing the colon from multi-spectral images. A preliminary study, in which the mucosal blood and collagen parameters were modified to reflect histopathological changes associated with colon cancer, has shown that the spectra predicted by our model resemble measured spectral reflectance of adenocarcinomas. This suggests that an extended model, which incorporates parameters corresponding to an abnormal colon, may be effective for differentiation between normal and cancerous tissues.

Algorithms↗

PubMed2005

Polynomial-time metrics for attributed trees.

We address the problem of comparing attributed trees and propose four novel distance measures centered around the notion of a maximal similarity common subtree. The proposed measures are general and defined on trees endowed with either symbolic or continuous-valued attributes and can be applied to rooted as well as unrooted trees. We prove that our measures satisfy the metric constraints and provide a polynomial-time algorithm to compute them. This is a remarkable and attractive property, since the computation of traditional edit-distance-based metrics is, in general, NP-complete, at least in the unordered case. We experimentally validate the usefulness of our metrics on shape matching tasks and compare them with (an approximation of) edit-distance.

Algorithms↗