We have combined photochemistry and photolithography with solid‐phase DNA synthesis chemistry to form a new technology that makes high density oligonucleotide probe array synthesis possible. Hybridization to these two‐dimensional arrays containing hundreds or thousands of oligonucleotide probes provides a powerful DNA sequence analysis tool. Two types of light‐generated DNA probe arrays have been used to test for a variety of mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. One array, made up of 428 probes, was designed to scan through the length of CFTR exon 11 and identify differences from the wild type reference sequence. The second type of array contained 1480 probes chosen to detect known deletions, insertions, or base substitution mutations. The validity of the probe arrays was established by hybridizing them with fluorescently labeled control oligonucleotide targets. Characterized mutant CFTR genomic DNA samples were then used to further test probe array hybridization specificity. Finally, ten unknown patient samples were genotyped using the CFTR probe array assay. The genotype assignments were identical to those obtained by PCR product restriction fragment analysis. Our results show that light‐generated DNA probe arrays are highly effective in analyzing complex mutation and polymorphism patterns in a relatively large gene such as CFTR. © 1996 Wiley‐Liss, Inc.

X-ray detectors in clinical computed tomography (CT) usually operate in current-integrating mode. Their complicated signal statistics often lead to intractable likelihood functions for practical use in model-based image reconstruction (MBIR). It is therefore desirable to design simplified statistical models without losing the essential factors. Depending on whether the CT transmission data are logarithmically transformed, pre-log and post-log models are two major categories of choices in CT MBIR. Both being approximations, it remains an open question whether one model can notably improve image quality over the other on real scanners. In this study, we develop and compare several pre-log and post-log MBIR algorithms under a unified framework. Their reconstruction accuracy based on simulation and clinical datasets are evaluated. The results show that pre-log MBIR can achieve notably better quantitative accuracy than post-log MBIR in ultra-low-dose CT, although in less extreme cases, post-log MBIR with handcrafted pre-processing remains a competitive alternative. Pre-log MBIR could play a growing role in emerging ultra-low-dose CT applications.

A TV minimization strategy incorporated into commonly used PET reconstruction algorithms was useful for reducing the occurrence of artifacts due to gaps between detector modules in small-diameter PET scanners.

The spatial resolution from Compton cameras suffers from measurement uncertainties in interaction positions and energies. The degree of degradation in spatial resolution is shift-variant (SV) over the field-of-view (FOV) because the imaging principle is based on the conical surface integration. In our study, the shift-variant point spread function (SV-PSF) is derived from point source measurements at various positions in the FOV and is incorporated into the system matrix of a fully three-dimensional, accelerated reconstruction, i.e. the listmode ordered subset expectation maximization (LMOSEM) algorithm, for resolution recovery. Simulation data from point sources were used to estimate SV and asymmetric parameters for Gaussian, Cauchy, and general parametric PSFs. Although little difference in the fitness accuracy between Gaussian and general parametric PSFs was observed, the general parametric model showed greater flexibility over the FOV in shaping the curve between that for Gaussian and Cauchy functions. The estimated asymmetric SV-PSFs were incorporated into the LMOSEM for resolution recovery. For simulation data from a single point source at the origin, all LMOSEM-SV-PSFs improved the spatial resolution by 2.6 times over the standard LMOSEM. For two point-source simulations, reconstructions also gave a two-fold improvement in spatial resolution and resulted in a greater recovered activity ratio at different positions in the FOV.