Browsing by Subject "Sensitivity and specificity"

Now showing 1 - 4 of 4

Open Access
Current constrained voltage scaled reconstruction (CCVSR) algorithm for MR-EIT and its performance with different probing current patterns
(Institute of Physics Publishing, 2003) Birgül, Ö.; Eyüboğlu, B. M.; İder, Y. Z.
Conventional injected-current electrical impedance tomography (EIT) and magnetic resonance imaging (MRI) techniques can be combined to reconstruct high resolution true conductivity images. The magnetic flux density distribution generated by the internal current density distribution is extracted from MR phase images. This information is used to form a fine detailed conductivity image using an Ohm's law based update equation. The reconstructed conductivity image is assumed to differ from the true image by a scale factor. EIT surface potential measurements are then used to scale the reconstructed image in order to find the true conductivity values. This process is iterated until a stopping criterion is met. Several simulations are carried out for opposite and cosine current injection patterns to select the best current injection pattern for a 2D thorax model. The contrast resolution and accuracy of the proposed algorithm are also studied. In all simulation studies, realistic noise models for voltage and magnetic flux density measurements are used. It is shown that, in contrast to the conventional EIT techniques, the proposed method has the capability of reconstructing conductivity images with uniform and high spatial resolution. The spatial resolution is limited by the larger element size of the finite element mesh and twice the magnetic resonance image pixel size.
Open Access
Fast and accurate mapping of complete genomics reads
(Academic Press, 2015) Lee, D.; Hormozdiari, F.; Xin, H.; Hach, F.; Mutlu, O.; Alkan C.
Many recent advances in genomics and the expectations of personalized medicine are made possible thanks to power of high throughput sequencing (HTS) in sequencing large collections of human genomes. There are tens of different sequencing technologies currently available, and each HTS platform have different strengths and biases. This diversity both makes it possible to use different technologies to correct for shortcomings; but also requires to develop different algorithms for each platform due to the differences in data types and error models. The first problem to tackle in analyzing HTS data for resequencing applications is the read mapping stage, where many tools have been developed for the most popular HTS methods, but publicly available and open source aligners are still lacking for the Complete Genomics (CG) platform. Unfortunately, Burrows-Wheeler based methods are not practical for CG data due to the gapped nature of the reads generated by this method. Here we provide a sensitive read mapper (sirFAST) for the CG technology based on the seed-and-extend paradigm that can quickly map CG reads to a reference genome. We evaluate the performance and accuracy of sirFAST using both simulated and publicly available real data sets, showing high precision and recall rates.
Open Access
A hybrid classification model for digital pathology using structural and statistical pattern recognition
(Institute of Electrical and Electronics Engineers, 2013) Ozdemir, E.; Gunduz-Demir, C.
Cancer causes deviations in the distribution of cells, leading to changes in biological structures that they form. Correct localization and characterization of these structures are crucial for accurate cancer diagnosis and grading. In this paper, we introduce an effective hybrid model that employs both structural and statistical pattern recognition techniques to locate and characterize the biological structures in a tissue image for tissue quantification. To this end, this hybrid model defines an attributed graph for a tissue image and a set of query graphs as a reference to the normal biological structure. It then locates key regions that are most similar to a normal biological structure by searching the query graphs over the entire tissue graph. Unlike conventional approaches, this hybrid model quantifies the located key regions with two different types of features extracted using structural and statistical techniques. The first type includes embedding of graph edit distances to the query graphs whereas the second one comprises textural features of the key regions. Working with colon tissue images, our experiments demonstrate that the proposed hybrid model leads to higher classification accuracies, compared against the conventional approaches that use only statistical techniques for tissue quantification. © 2012 IEEE.
Open Access
A sensitive and selective ratiometric near IR fluorescent probe for zinc ions based on the distyryl-bodipy fluorophore
(2008) Atilgan, S.; Ozdemir, T.; Akkaya, E. U.
(Chemical Equation Presented) A novel distyryl-substituted boradiazaindacene (bodipy) dye with an emission peak moving hypsochromically from 730 to 680 nm on Zn(II) ion binding seems to be promising as one of the very few water-soluble fluorescent chemosensors emitting in the near IR region. © 2008 American Chemical Society.