Jin Hyeong Park

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We propose methods for outlier handling and noise reduction using weighted local linear smoothing for a set of noisy points sampled from a nonlinear manifold. Weighted PCA is used as a building block for our methods and we suggest an iterative weight selection scheme for robust local linear fitting together with an outlier detection method based on minimal(More)
We propose a fully automatic system for cardiac view classification of echocardiogram. Given an echo study video sequence, the system outputs a view label among the pre-defined standard views. The system is built based on a machine learning approach that extracts knowledge from an annotated database. It characterizes three features: 1) integrating local and(More)
Various forms of additive modeling techniques have been successfully used in many data mining and machine learning–related applications. In spite of their great success, boosting algorithms still suffer from a few open-ended problems that require closer investigation. The efficiency of any additive modeling technique relies significantly on the choice of(More)
In this paper, we propose a robust motion segmentation method based on the matrix factorization and subspace separation. We, first, mathematically prove that the shape interaction matrix can be derived using QR decomposition rather than Singular Value Decomposition(SVD). Using shape interaction matrix, we solve the motion segmentation problem using spectral(More)
Doppler echocardiography is widely used for functional assessment of heart valves such as mitral valve. In current clinical work flow, to extract Doppler measurements, the envelopes of acquired Doppler spectra are manually traced. We propose a robust algorithm for automatically tracing the envelopes of mitral valve inflow Doppler spectra, which exhibit a(More)
Accurate detection and segmentation of anatomical structures from ultrasound images are crucial for clinical diagnosis and biometric measurements. Although ultrasound imaging has been widely used with superiorities such as low cost and portability, the fuzzy border definition and existence of abounding artifacts pose great challenges for automatically(More)
In this paper, we propose a new support vector clustering (SVC) strategy by combining (SVC) with spectral graph partitioning (SGP). SVC has two main steps: support vector computation and cluster labeling using adjacency matrix. Spectral graph partitioning (SGP) method is applied to the adjacency matrix to determine the cluster labels. It is feasible to(More)
In this study, the R7L10 peptide, which is composed of a 7-arginine stretch and a 10-leucine stretch, was evaluated as a carrier for the combined delivery of curcumin and plasmid DNA (pDNA) into the lungs. Curcumin is a natural product with anti-inflammatory and anti-tumor effects. Curcumin-loaded R7L10 (R7L10-curucmin) was prepared by an oil-in-water (O/W)(More)
Gene therapy has been considered a promising approach for glioblastoma therapy. To avoid side effects and increase the specificity of gene expression, gene expression should be tightly regulated. In this study, glioma and hypoxia dual-specific plasmids (pEpo-NI2-SV-Luc and pEpo-NI2-SV-HSVtk) were developed by combining the erythropoietin (Epo) enhancer and(More)