Sung Yun Park

Speckle noise reduction in ultrasound images using a discrete wavelet transform-based image fusion technique

Here, the speckle noise in ultrasonic images is removed using an image fusion-based denoising method. To optimize the denoising performance, each discrete wavelet transform (DWT) and filtering technique was analyzed and compared. In addition, the performances were compared in order to derive the optimal input conditions. To evaluate the speckle noise removal performance, an image fusion algorithm was applied to the ultrasound images, and comparatively analyzed with the original image without the algorithm. As a result, applying DWT and filtering techniques caused information loss and noise characteristics, and did not represent the most significant noise reduction performance. Conversely, an image fusion method applying SRAD-original conditions preserved the key information in the original image, and the speckle noise was removed. Based on such characteristics, the input conditions of SRAD-original had the best denoising performance with the ultrasound images. From this study, the best denoising technique proposed based on the results was confirmed to have a high potential for clinical application.

Comparison of Epidermal/Dermal Damage Between the Long-Pulsed 1064 nm Nd:YAG and 755 nm Alexandrite Lasers Under Relatively High Fluence Conditions: Quantitative and Histological Assessments

OBJECTIVE The purpose of this study was to compare degrees of epidermal/dermal tissue damage quantitatively and histologically after laser irradiation, to find ideal treatment conditions with relatively high fluence for skin rejuvenation. BACKGROUND DATA A number of recent studies have evaluated the clinical efficacy and safety of therapeutic lasers under relatively low fluence conditions. METHODS We transmitted the long-pulsed 1064 nm Nd:YAG and 755 nm Alexandrite lasers into pig skin according to different fluences and spot diameters, and estimated epidermal/dermal temperatures. Pig skin specimens were stained with hematoxylin and eosin for histological assessments. The fluence conditions comprised 26, 30, and 36 J/cm2, and the spot diameter conditions were 5, 8, and 10 mm. Pulse duration was 30 ms for all experiments. RESULTS Both lasers produced reliable thermal damage on the dermis without any serious epidermal injuries, under relatively high fluence conditions. The 1064 nm laser provided more active fibrous formations than the 755 nm laser, while higher risks for tissue damages simultaneously occurred. CONCLUSIONS The ideal treatment conditions for skin rejuvenation were 8 mm diameter with 30 J/cm2 and 10 mm diameter with 26 J/cm2 for the 1064 nm laser, and 8 mm diameter with 36 J/cm2 and 10 mm diameter with 26 J/cm2 for the 755 nm laser.

A Study on a Bio-signal Biometric Algorithm on the Ubiquitous Environments

This paper is about the personal identification algorithm for adapting ubiquitous environment using electrocardiogram (ECG) that has been studied by a few researchers recently. The main characteristic of proposed algorithm uses together features analysis and morphological analysis method. The Principle Component Analysis (PCA) algorithm was applied for morphological analysis method and the features analysis method adapting to Support Vector Machine (SVM) classifier algorithm. We choose 18 ECG files from MIT-BIH Normal Sinus Rhythm Database for estimating algorithm performance. The algorithm extracts 100 heartbeats from each ECG file, and use 40 heartbeats for training and 60 heartbeats for testing. The proposed algorithm shows clearly superior performance in all ECG data, amounting to 93.89% heartbeat recognition rate and 100% ECG recognition rate.

An analysis of contrast agent flow patterns from sequential ultrasound images using a motion estimation algorithm based on optical flow patterns.

This study estimates flow patterns of contrast agents from successive ultrasound image sequences by using an anisotropic diffusion-based optical flow algorithm. Before flow fields were recovered, the test sequences were reconstructed using relative composition of structural and textural parts from the original image. To improve estimation performance, an anisotropic diffusion filtering model was embedded into a spline-based slightly nonconvex total variation-L1 minimization algorithm. In addition, an incremental coarse-to-fine warping framework was employed with a linear minimization scheme to account for a large displacement. After each warping iteration, the implementation used intermediate bilateral filtering to prevent oversmoothing across motion boundaries. The performance of the proposed algorithm was tested using three different sequences obtained from two simulated datasets and phantom ultrasound sequences. The results indicate the robust performance of the proposed method under different noise environments. The results of the phantom study also demonstrate reliable performance according to different injection conditions of contrast agents. These experimental results suggest the potential clinical applicability of the proposed algorithm to ultrasonographic diagnosis based on contrast agents.

ANALYSIS OF THE THERAPEUTIC EFFECTS ON SKIN REJUVENATION FOR THE DIFFERENT TREATMENT CONDITIONS OF 1064 nmNd:YAG LASER: SIMULATION AND PHANTOM STUDY

In this study, we analyzed internal and external skin temperatures as well as penetration depths for the different treatment conditions regarding the 1064 nm Nd:YAG laser to find the optimum treatment condition for skin rejuvenation. We transmitted the laser into a skin mimicking phantom with laser fluence conditions of 26, 30 and 36 J/cm2, and spot diameter conditions of 8 and 10 mm. We also selected the pulse duration as 30 ms, and measured internal–external skin temperatures and penetration depths. To examine the distribution of internal–external skin temperatures, we performed a heat transfer analysis based on the finite element method. Skin layers were designed as three-dimensional models to predict skin temperatures more accurately. We employed the same laser conditions of fluence and spot diameter while performing actual and simulation analyses. Consequently, we found that laser conditions for a spot diameter of 8 mm with a fluence of 36 J/cm2 and a spot diameter of 10 mm with a fluence of 26 and 30 J/cm2 demonstrate the greatest effectiveness toward skin rejuvenation. Moreover, the penetration depths and the range of thermal distribution increased as the fluence and spot diameter increased. In particular, the spot diameter influenced the therapeutic effects more seriously than the fluence.

Feasibility Study of Non-linear Apodization for IVUS B-mode Imaging

This paper evaluates the performance of the non-linear apodization technique at the ultrasound B-mode (Brightness mode) image and indirectly demonstrates feasibility at the IVUS (Intravascular ultrasound) imaging application by changing coordinate condition. We conducted simulation with dedicated sound field programs (Field II and MATLAB), and the rectangular window and the Kaiser windows with two different control parameters were used for tri-apodization as an example of the non-linear apodization. The measurements of −6 dB main-lobe width and side-lobe level at the region of interest (ROI) were performed, and the point target simulation results show that tri-apodization had almost similar −6 dB main-lobe width and 6 dB lower side-lobe level in comparison of the result of the rectangular window. Therefore, this technique can be applied to IVUS B-mode image to improve image quality.

Predicting Osteoporosis by Analyzing Fracture Risk Factors and Trabecular Microarchitectures of the Proximal Femur from DXA Images

This study aimed to identify the optimal threshold ranges for predicting osteoporosis and osteoporotic fractures by analyzing the correlations between trabecular patterns and fracture risk factors. We selected 85 post-menopausal women as experimental subjects and classified them into 29 normal and 56 osteoporotic groups. We proposed a novel thresholding algorithm that divides the threshold ranges from 0 to 95% based on trabecular bone area and assessed osteoporosis predictability for each range. Evaluation parameters were categorized into morphological parameters (Tb.Area, Sk.Length and fractal dimension) and fracture risk factors (MSCT, LSCT, FNW, TW, FNAL and HAL). Consequently, we found the clinical usefulness of our algorithm for discriminating patients with osteoporosis from those with normal bone. The significances between the morphological parameters and the fracture risk factors improved as bone mineral density decreased. Based on these results, we selected the optimal threshold conditions for predicting osteoporosis and osteoporotic fractures at thresholds of 40-80%.

A Simulation Study of the Treatment Effects for the 1064 nm Nd:YAG Laser under Various Fluence and Pulse Durations

The purpose of this study was to analyze treatment effect for skin aging according to changes of fluence and pulse duration of 1064nm Nd:YAG laser. For this purpose, we designed skin model composed of epidermis, dermis, and fat, and each layer had similar thickness of facial skin. Environmental temperature was set to 26°C, and the initial temperature of each skin layer was designated as human body temperature (36.5°C). The fluence of the treatment laser was divided into 8, 9 and 10J/cm2, and the pulse duration was classified to 0.35, 0.50, 0.70 and 1.00ms, respectively. Based on experimental results, we found that the skin temperature increased along with penetration depth as increase in fluence. In addition, the treatment condition with fluence of 8J/cm2 and pulse duration of 0.7ms, as well as fluence of 9J/cm2 and pulse duration of 0.5ms, transmitted the heat into the dermis most effectively without any skin damage.

Application of Artificial Neural Networks for Diagnosing Acute Appendicitis

The purpose of this study is to develop an appendicitis diagnosis system, by using artificial neural networks (ANNs). Acute appendicitis is one of the most common surgical emergencies of the abdomen. Various methods have been developed to diagnose appendicitis, but these methods have not shown good performance in the Middle East and Asia, or even in the West. We used the structures of ANNs with 801 patients. These various structures are a multilayer neural network structure (MLNN), a radial basis function neural network structure (RBF), and a probabilistic neural network structure (PNN). The Alvarado clinical scoring system was used for comparison with the ANNs. The accuracy of MLNN, RBF, PNN, and Alvarado was 97.84%, 99.80%, 99.41% and 72.19%, respectively. The AUC of MLNN, RBF, PNN, and Alvarado was 0.985, 0.998, 0.993, and 0.633, respectively. The performance of ANNs was significantly better than the Alvarado clinical scoring system (P<0.001). The models developed to diagnose appendicitis using ANNs showed good performance. We consider that the developed models can help junior clinical surgeons diagnose appendicitis.

A Study on Measurement of Photoplethysmograph Using a Smartphone Camera

In this study, we proposed a method for measuring photoplethysmographic using a smartphone camera. A development algorithm is consists 6 procedures. The first is to convert RGB to Gray level from a camera image, the second is to detect ROI from image, the third is to extract photoplethysmography signal from a camera image, the fourth is to filter baseline, and the last is to oversample procedure using cubic spline interpolation. The proposed algorithm has been tested using several smartphone with a person and which can effectively acquire persons PPG signal at any situation. We supposed that the proposed algorithm can easily adapt for a smartphone m-health system.