Biomedical subjects

Moshe Israeli

Publications and source records attributed to Moshe Israeli.

3 recordsLinked to original sources

PubMed2005

Pseudopolar-based estimation of large translations, rotations, and scalings in images.

One of the major challenges related to image registration is the estimation of large motions without prior knowledge. This paper presents a Fourier-based approach that estimates large translations, scalings, and rotations. The algorithm uses the pseudopolar (PP) Fourier transform to achieve substantial improved approximations of the polar and log-polar Fourier transforms of an image. Thus, rotations and scalings are reduced to translations which are estimated using phase correlation. By utilizing the PP grid, we increase the performance (accuracy, speed, and robustness) of the registration algorithms. Scales up to 4 and arbitrary rotation angles can be robustly recovered, compared to a maximum scaling of 2 recovered by state-of-the-art algorithms. The algorithm only utilizes one-dimensional fast Fourier transform computations whose overall complexity is significantly lower than prior works. Experimental results demonstrate the applicability of the proposed algorithms.

Algorithms↗

PubMed2005

Spatial phase-shift interferometry--a wavefront analysis technique for three-dimensional topometry.

We describe a new wavefront analysis method, in which certain wavefront manipulations are applied to a spatially defined area in a certain plane along the optical axis. These manipulations replace the reference-beam phase shifting of existing methods, making this method a spatial phase-shift interferometry method. We demonstrate the system's dependence on a defined spatial Airy number, which is the ratio of the characteristic dimension of the manipulated area and the Airy disk diameter of the optical system. We analytically obtain the resulting intensity data of the optical setup and develop various methods to accurately reconstruct the inspected wavefront out of the data. These reconstructions largely involve global techniques, in which the entire wavefront's pattern affects the reconstruction of the wavefront in any given position. The method's noise sensitivity is analyzed, and actual reconstruction results are presented.

Journal Article↗

PubMed2005

Hematopoietic chimerism monitoring based on STRs: quantitative platform performance on sequential samples.

Hematopoietic stem cell transplantation (HSCT) creates a donor-recipient cellular chimerism in the patient, which is quantitatively assayed from peripheral blood based on STR-DNA. Since chimerism values often vary across a patient's samples, it is important to determine to what extent this variability reflects technical aspects of platform performance. This issue is systematically assessed in the current study for the first time. Using the SGM Plus multiplex PCR kit and ABI platform, the longitudinal performance of STR markers was quantitatively evaluated in two chimeric models with true values, and in patient samples (n >500 marker loci). Computation of percent chimerism for each marker, and mean (sample) percent chimerism, standard deviation, and coefficient of variance was performed by our ChimerTrack utility. In chimeric models with known values, individual markers exhibited an accuracy (observed/true) of 88-98%; replication precision was 92-100% true, with a mean error of 2%. Fragment size calling was greater than 99% accurate and precise. Patient results were comparable for markers, relaive to sample means. One source of technical variability in chimerism estimation was allelic differential amplification efficiency. The latter was influenced by signal amplitude, dye label, marker size, and allelic size interval. It can be concluded that long-term chimeric tracking is routinely feasible using this platform in conjunction with ChimerTrack software. Importantly, mean percent chimerism, for any sample, should closely approximate the true chimeric status, with a technical accuracy of 98%. Guidelines are presented for selecting an optimized marker profile.

Alleles↗