A robust and computationally efficient algorithm for automated tracking of high densities of particles travelling in (semi-) straight lines is presented. It extends the implementation of (Sbalzarini and Koumoutsakos 2005) and is intended for use in the analysis of single ion track detectors. By including information of existing tracks in the exclusion criteria and a recursive cost minimization function, the algorithm is robust to variations on the measured particle tracks. A trajectory relinking algorithm was included to resolve the crossing of tracks in high particle density images. Validation of the algorithm was performed using fluorescent nuclear track detectors (FNTD) irradiated with high- and low (heavy) ion fluences and showed less than 1% faulty trajectories in the latter.

The nerve fiber bundles constitutive of the white matter in the brain are organized in such a way that they exhibit a certain degree of structural anisotropy and birefringence. The birefringence exhibited by such aligned fibrous tissue is known to be extremely sensitive to small pathological alterations. Indeed, highly aligned anisotropic fibers exhibit higher birefringence than structures with weaker alignment and anisotropy, such as cancerous tissue. In this study, we performed experiments on thick coronal slices of a healthy human brain to explore the possibility of (i) measuring, with a polarimetric microscope the birefringence exhibited by the white matter and (ii) relating the measured birefringence to the fiber orientation and the degree of alignment. This is done by analyzing the spatial distribution of the degree of polarization of the backscattered light and its variation with the polarization state of the probing beam. We demonstrate that polarimetry can be used to reliably distinguish between white and gray matter, which might help to intraoperatively delineate unstructured tumorous tissue and well organized healthy brain tissue. In addition, we show that our technique is able to sensitively reconstruct the local mean nerve fiber orientation in the brain, which can help to guide tumor resections by identifying vital nerve fiber trajectories thereby improving the outcome of the brain surgery.

Interpreting the polarimetric data from fiber-like macromolecules constitutive of tissue can be difficult due to strong scattering. In this study, we probed the superficial layers of fibrous tissue models (membranes consisting of nanofibers) displaying varying degrees of alignment. To better understand the manifestation of membranes' degree of alignment in polarimetry, we analyzed the spatial variations of the backscattered light's Stokes vectors as a function of the orientation of the probing beam's linear polarization. The degree of linear polarization reflects the uniaxially birefringent behavior of the membranes. The rotational (a-)symmetry of the backscattered light's degree of linear polarization provides a measure of the membranes' degree of alignment.