The fluorescence lifetime technique offers an effective way to resolve fluorescent components with overlapping emission spectra. The presence of multiple fluorescent components in biological compounds can hamper their discrimination. The conventional method based on the nonlinear least-squares technique is unable to consistently determine the correct number of fluorescent components in a fluorescence decay profile. This can limit the applications of the fluorescence lifetime technique in biological assays and diagnoses where more than one fluorescent component is typically encountered. We describe the use of an expectation-maximization (EM) method with joint deconvolution to estimate the fluorescence decay parameters, and the Bayesian information criterion (BIC) to accurately determine the number of fluorescent components. A comprehensive simulation and experimental study is carried out to compare the performance and accuracy of the proposed method. The results show that the EM-BIC method is able to accurately identify the correct number of fluorescent components in samples with weakly fluorescing components.
This work investigates the use of optical coherence tomography (OCT) to identify virus infection in orchid plants. Besides revealing the cross-sectional structure of orchid leaves, highly scattering upper leaf epidermides are detected with OCT for virus-infected plants. This distinct feature is not observable under histological examination of the leaf samples. Furthermore, the leaf epidermides of stressed but healthy plants, which exhibit similar visual symptoms as virus-infected plants, are not highly scattering and are similar to those of healthy plants. The results suggest that virus-infected orchid plants can be accurately identified by imaging the epidermal layers of their leaves with OCT. The OCT modality is suitable for fast, nondestructive diagnosis of orchid virus infection, which may potentially lead to significant cost savings and better control of the spread of viruses in the orchid industry.
In this paper, we address the problem of spectral data sampling in Fourier domain optical coherence
tomography (FD-OCT). The interferometric information in a Fourier Domain OCT system is retrieved from spectral
measurements made using a linear array spectrometer. In such spectrometers, spectral data are available as an array
of points equally spaced in the wavelength domain. To obtain the spatial profile, the spectral data have to be
converted to the frequency domain before applying the Fourier transform. The inverse relationship between these
domains causes an unequal spacing of data points after the spectral data is converted to the frequency domain,
resulting in the degradation of the FD-OCT images. The current practice typically utilizes zero-padding and spline
interpolation to circumvent this problem. While these algorithms do improve the FD-OCT images, our
investigations showed that more can be done to enhance the images. Toward this end, we propose a signal
processing algorithm based on non-uniform discrete Fourier transform (NUDFT). The results of our algorithm are
compared against the current algorithms on both simulated and experimental results.
Estimation of the tissue optical characteristics using optical coherence tomography (OCT) requires good modeling.
Present modeling of the system includes effects such as scattering of light in tissues. However, absorption effects were
often neglected in the model. They may be significant depending on the tissue type and the wavelength of the light
source. We present a study where the effects of absorption in light propagation in biological tissue were examined in the
theoretical modeling of OCT based on the single-scattering model. OCT M-scans were performed on liquid tissue
phantoms at 1% concentration. In order to mimic the effects of absorption, India ink was added to the solution. Different
concentrations of Indian ink were used to vary the absorption coefficient in the tissue phantoms. Estimation of the
absorption, scattering coefficients from the OCT signal were obtained. Substantial reduction in the slope of the
logarithmic OCT signal was observed when India ink was introduced to the liquid tissue phantoms. The results suggest
that the effects of the absorption clearly affected the estimation of the overall extinction coefficient. In order to improve
the accuracy of estimation of these characteristics, absorption effects should be taken into account.
For copyright protection, the robustness of a watermarking scheme against various attacks is an essential requirement. Many proposed robust watermarking schemes may achieve good robustness but at the expense of sacrificing the good quality of the watermarked image. This work, therefore, proposes a transparent robust watermarking scheme, which embeds the watermark (or the secret information) adaptively in the discrete cosine transform (DCT) domain. The proposed scheme is blind as the original image is not needed, and only an image-dependent dual key containing the watermark locations and the scaling factors is required for watermark extraction. This content adaptive replacement embedding technique can guarantee preservation of good visual quality of a watermarked image. The watermarking scheme is shown to be highly robust for a wide range of attacks, including JPEG compression, quantization, additive noise, rotation, cropping, scaling, and filtering. Compared with other existing DCT-domain watermarking methods, the proposed watermarking method can achieve higher robustness performance, while retaining better quality of the watermarked image.
Bladder cancer is the fourth common malignant disease worldwide, accounting for 4% of all cancer cases. In Singapore, it is the ninth most common form of cancer. The high mortality rate can be reduced by early treatment following precancerous screening. Currently, the gold standard for screening bladder tumors is histological examination of biopsy specimen, which is both invasive and time-consuming. In this study ex vivo urine fluorescence cytology is investigated to offer a timely and biopsy-free means for detecting bladder cancers. Sediments in patients' urine samples were extracted and incubated with a novel photosensitizer, hypericin. Laser confocal microscopy was used to capture the fluorescence images at an excitation wavelength of 488 nm. Images were subsequently processed to single out the exfoliated bladder cells from the other cells based on the cellular size. Intensity histogram of each targeted cell was plotted and feature vectors, derived from the histogram moments, were used to represent each sample. A difference in the distribution of the feature vectors of normal and low-grade cancerous bladder cells was observed. Diagnostic algorithm for discriminating between normal and low-grade cancerous cells is elucidated in this paper. This study suggests that the fluorescence intensity profiles of hypericin in bladder cells can potentially provide an automated quantitative means of early bladder
cancer diagnosis.
This paper presents a system for automatic recognition of Integrated Circuit chips on assembled circuit boards by recognizing characters on its package label. The paper concentrates on the extraction and recognition of these character. The extraction of characters involves binarization of the image, character localization, orientation alignment and character re-sizing. A pre-trained two-layer feed-forward neural network is used to recognize the extracted characters. The neural network is trained using the back-propagation method. Experimental results are presented.
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