Remote optical sensing and quantification of single analyte molecules in liquids through a waveguide

In the work at hand a novel method to detect and quantify single oligonucleotide molecules in liquids is introduced. The aim consists of rapid specific quantification of mRNA molecules in solutions at room temperature by applying free-floating fluorescent molecular switches as integral part of an optical biosensor. The implementation of molecular switches enables the sensor to specifically detect unlabelled oligonucleotide sequences. In the thesis the crucial components consisting of the detection algorithm, the optical setup and the molecular switches (molecular beacons) are elaborated. In order to be able to detect single fluorescent bursts in solutions the necessary software has to be developed. Herefore a method for the unambiguous detection of transient burst-like signals in presence of significant stationary noise is described. In order to discriminate a transient signal from the background noise an optimum threshold is determined using an iterative algorithm that isolates the probability distribution of the background noise. Knowledge of the probability distribution of the noise allows excluding the detection of false positive events with a defined probability. The method can be applied to the detection of transient single-molecule fluorescence events in presence of a strong background. Using this peak detection method the sensing of single oligo-FRET molecules in buffer solution through a cleaved single mode optical fiber is demonstrated. Both the excitation light and the fluorescence signal are coupled through the same fiber thus implementing a remote detection scheme. The background luminescence created in the glass fiber by the strong excitation light is largely suppressed by the use of a wavelength-shifting concept. Fluorescence bursts are observed by proper stirring of the test solution. In addition, a discussion of the detection efficiency of the cleaved fiber by means of dipole radiation patterns near the glass/water interface is offered. In a next step the optimal operation conditions of the setup are described and investigated by varying the relevant parameters over a wide range. This indicates the optimum values for the stirring velocity, the excitation intensity, the bin width and the experiment duration. In the next step single molecule detection of oligonucleotide FRET constructs in liquids through a single-mode fiber is applied using the optimal detection conditions, which only then allows for quantification of ultra-low concentrations. A linear dependence of the number of detected fluorescence bursts on the concentration of the test solution over a wide dynamic range is demonstrated, starting at pM down to 1aM concentrations. This qualifies the algorithm and the apparatus to be applied in quantitative sensing applications and establishes the software and hardware elements as a functional unity. Finally the molecular switches are implicated into the system. The application of molecular beacons to specific detection and quantification of characteristic mRNA sequences in a test solution is demonstrated. In bulk experiments, the performance of the molecular beacons is checked. It is found that single base pair mismatches between beacon and target sequence can be detected through the analysis of melting curves. Single-molecule experiments performed using the optical setup with molecular beacons in absence of targets show that only a negligible fraction of beacons is open at room temperature and produce fluorescence bursts. Upon addition of perfect targets the number of detected bursts increases dramatically. A linear dependence of the number of fluorescence bursts as a function of the concentration of molecular beacon-target sequence duplexes is observed. Furthermore, for a fixed concentration of molecular beacons, a linear increase of the number of bursts as a function of the target sequence concentration can be observed

Segmentation of ultrasound images of thyroid nodule for assisting fine needle aspiration cytology

The incidence of thyroid nodule is very high and generally increases with the age. Thyroid nodule may presage the emergence of thyroid cancer. The thyroid nodule can be completely cured if detected early. Fine needle aspiration cytology is a recognized early diagnosis method of thyroid nodule. There are still some limitations in the fine needle aspiration cytology, and the ultrasound diagnosis of thyroid nodule has become the first choice for auxiliary examination of thyroid nodular disease. If we could combine medical imaging technology and fine needle aspiration cytology, the diagnostic rate of thyroid nodule would be improved significantly. The properties of ultrasound will degrade the image quality, which makes it difficult to recognize the edges for physicians. Image segmentation technique based on graph theory has become a research hotspot at present. Normalized cut (Ncut) is a representative one, which is suitable for segmentation of feature parts of medical image. However, how to solve the normalized cut has become a problem, which needs large memory capacity and heavy calculation of weight matrix. It always generates over segmentation or less segmentation which leads to inaccurate in the segmentation. The speckle noise in B ultrasound image of thyroid tumor makes the quality of the image deteriorate. In the light of this characteristic, we combine the anisotropic diffusion model with the normalized cut in this paper. After the enhancement of anisotropic diffusion model, it removes the noise in the B ultrasound image while preserves the important edges and local details. This reduces the amount of computation in constructing the weight matrix of the improved normalized cut and improves the accuracy of the final segmentation results. The feasibility of the method is proved by the experimental results.Comment: 15pages,13figure

Laser Ultrasound Inspection Based on Wavelet Transform and Data Clustering for Defect Estimation in Metallic Samples

Laser-generated ultrasound is a modern non-destructive testing technique. It has been investigated over recent years as an alternative to classical ultrasonic methods, mainly in industrial maintenance and quality control procedures. In this study, the detection and reconstruction of internal defects in a metallic sample is performed by means of a time-frequency analysis of ultrasonic waves generated by a laser-induced thermal mechanism. In the proposed methodology, we used wavelet transform due to its multi-resolution time frequency characteristics. In order to isolate and estimate the corresponding time of flight of eventual ultrasonic echoes related to internal defects, a density-based spatial clustering was applied to the resulting time frequency maps. Using the laser scan beam’s position, the ultrasonic transducer’s location and the echoes’ arrival times were determined, the estimation of the defect’s position was carried out afterwards. Finally, clustering algorithms were applied to the resulting geometric solutions from the set of the laser scan points which was proposed to obtain a two-dimensional projection of the defect outline over the scan plane. The study demonstrates that the proposed method of wavelet transform ultrasonic imaging can be effectively applied to detect and size internal defects without any reference information, which represents a valuable outcome for various applications in the industry. View Full-TextPeer ReviewedPostprint (published version