Microaneurysms (MAs) are known to be the early signs of diabetic retinopathy (DR). An automated MA detection system based on curvelet transform is proposed for color fundus image analysis. Candidates of MA were extracted in two parallel steps. In step one, blood vessels were removed from preprocessed green band image and preliminary MA candidates were selected by local thresholding technique. In step two, based on statistical features, the image background was estimated. The results from the two steps allowed us to identify preliminary MA candidates which were also present in the image foreground. A collection set of features was fed to a rule-based classifier to divide the candidates into MAs and non-MAs. The proposed system was tested with Retinopathy Online Challenge database. The automated system detected 162 MAs out of 336, thus achieved a sensitivity of 48.21% with 65 false positives per image. Counting MA is a means to measure the progression of DR. Hence, the proposed system may be deployed to monitor the progression of DR at early stage in population studies.
We demonstrate the in vivo assessment of human scars by parametric imaging of birefringence using polarization-sensitive optical coherence tomography (PS-OCT). Such in vivo assessment is subject to artifacts in the detected birefringence caused by scattering from blood vessels. To reduce these artifacts, we preprocessed the PS-OCT data using a vascular masking technique. The birefringence of the remaining tissue regions was then automatically quantified. Results from the scars and contralateral or adjacent normal skin of 13 patients show a correspondence of birefringence with scar type: the ratio of birefringence of hypertrophic scars to corresponding normal skin is 2.2 ± 0.2 (mean ± standard deviation ), while the ratio of birefringence of normotrophic scars to normal skin is 1.1 ± 0.4 . This method represents a new clinically applicable means for objective, quantitative human scar assessment.
An enhanced dental cavity diameter measurement mechanism using an intensity-modulated fiber optic displacement sensor (FODS) scanning and imaging system, fuzzy logic as well as a single-layer perceptron (SLP) neural network, is presented. The SLP network was employed for the classification of the reflected signals, which were obtained from the surfaces of teeth samples and captured using FODS. Two features were used for the classification of the reflected signals with one of them being the output of a fuzzy logic. The test results showed that the combined fuzzy logic and SLP network methodology contributed to a 100% classification accuracy of the network. The high-classification accuracy significantly demonstrates the suitability of the proposed features and classification using SLP networks for classifying the reflected signals from teeth surfaces, enabling the sensor to accurately measure small diameters of tooth cavity of up to 0.6 mm. The method remains simple enough to allow its easy integration in existing dental restoration support systems.
Bone regeneration is essential in medical treatment, such as in surgical bone healing and orthodontics. The aim of this study is to examine the effect of different powers of 940 nm diode low-level laser treatment (LLLT) on osteoblast cells during their proliferation and differentiation stages. A human fetal osteoblast cell line was cultured and treated with LLLT. The cells were divided into experimental groups according to the power delivered and periods of exposure per day for each laser power. The (3-(4,5-dimethylthiazol-2yl)-2,5 diphenyl tetrazolium bromide) (MTT) assay was used to determine cell proliferation. Both alkaline phosphatase and osteocalcin activity assays were assessed for cell differentiation. All treatment groups showed a significant increase in cell proliferation and differentiation compared to the control group. Regarding the exposure time, the subgroups treated with the LLLT for 6 min showed higher proliferation and differentiation rates for the powers delivered, the 300-mW LLLT group significantly increased the amount of cell proliferation. By contrast, the 100 and 200 mW groups showed significantly greater amounts of cell differentiation. These results suggest that the use of LLLT may play an important role in stimulating osteoblast cells for improved bone formation.
The purpose of this study is to investigate the potential of intensity modulated fiber optic displacement sensor scanning system for the imaging of dental cavity. Here, we discuss our preliminary results in the imaging of cavities on various teeth surfaces, as well as measurement of the diameter of the cavities which are represented by drilled holes on the teeth surfaces. Based on the analysis of displacement measurement, the sensitivities and linear range for the molar, canine, hybrid composite resin, and acrylic surfaces are obtained at 0.09667 mV/mm and 0.45 mm; 0.775 mV/mm and 0.4 mm; 0.5109 mV/mm and 0.5 mm; and 0.25 mV/mm and 0.5 mm, respectively, with a good linearity of more than 99%. The results also show a clear distinction between the cavity and surrounding tooth region. The stability, simplicity of design, and low cost of fabrication make it suitable for restorative dentistry.
The goal of this study is to assess the risk of overexposure, when DFB dye laser is used for medical treatment in pulsed mode operation. Results of experimental study showing an unexpected rise of energy in pulses of distributed feedback dye laser (DFDL) output due to temperature phase gratings in dye cell during passively Q switched and mode-locked operation is reported. This unintended increase in the number of pulses, pulse duration, per pulse energy may cause side effects, when used for selective photothermolysis. To probe this phenomenon the most commonly used Rh6G dye was excited with 10-20 pulses of second harmonic of a passively Q switched and mode-locked Nd:yttrium-aluminum-garnet(YAG) laser. The outputs of DFDL and Nd:YAG laser were recorded by an Imacon-675 streak camera. The peak of DFDL output pulses was found delayed proportionally from the peak of the Nd:YAG pulses by more than an interpulse period of excitation laser. A computer program was used to simulate the experimentally measured results to estimate the thermal decay constants and energy retained by medium. The delay between peaks of Nd:YAG (input) and DFDL (output) pulses was found to vary from 10 to 14 ns for various cavity lengths. It was interesting to note that for smaller inter-pulse periods the effect of gradual gain buildup satisfied the threshold conditions for some of the pulses that otherwise cannot lase. This may lead to unintended increase in energy fluence causing overexposure-induced bio effects.
Fourier transform infrared (FTIR) spectroscopy technique can detect the abnormality of a cervical cell that occurs before the morphological change could be observed under the light microscope as employed in conventional techniques. This paper presents developed features extraction for an automated screening system for cervical precancerous cell based on the FTIR spectroscopy as a second opinion to pathologists. The automated system generally consists of the developed features extraction and classification stages. Signal processing techniques are used in the features extraction stage. Then, discriminant analysis and principal component analysis are employed to select dominant features for the classification process. The datasets of the cervical precancerous cells obtained from the feature selection process are classified using a hybrid multilayered perceptron network. The proposed system achieved 92% accuracy.
This paper presents a fiber Bragg grating (FBG)-instrumented prosthetic silicone liner that provides cushioning for the residual limb and can successfully measure interface pressures inside prosthetic sockets of lower-limb amputees in a simple and practical means of sensing. The liner is made of two silicone layers between which 12 FBG sensors were embedded at locations of clinical interest. The sensors were then calibrated using a custom calibration platform that mimics a real-life situation. Afterward, a custom gait simulating machine was built to test the liner performance during an amputee's simulated gait. To validate the findings, the results were compared to those obtained by the commonly used F-socket mats. As the statistical findings reveal, both pressure mapping methods measured the interface pressure in a consistent way, with no significant difference (P-values ≥0.05). This pressure mapping technique in the form of a prosthetic liner will allow prosthetics professionals to quickly and accurately create an overall picture of the interface pressure distribution inside sockets in research and clinical settings, thereby improving the socket fit and amputee's satisfaction.
Intravascular optical coherence tomography (OCT) is an optical imaging modality commonly used in the assessment of coronary artery diseases during percutaneous coronary intervention. Manual segmentation to assess luminal stenosis from OCT pullback scans is challenging and time consuming. We propose a linear-regression convolutional neural network to automatically perform vessel lumen segmentation, parameterized in terms of radial distances from the catheter centroid in polar space. Benchmarked against gold-standard manual segmentation, our proposed algorithm achieves average locational accuracy of the vessel wall of 22 microns, and 0.985 and 0.970 in Dice coefficient and Jaccard similarity index, respectively. The average absolute error of luminal area estimation is 1.38%. The processing rate is 40.6 ms per image, suggesting the potential to be incorporated into a clinical workflow and to provide quantitative assessment of vessel lumen in an intraoperative time frame.