Hyunjin Park

There have been significant efforts to build a probabilistic atlas of the brain and to use it for many common applications, such as segmentation and registration. Though the work related to brain atlases can be applied to nonbrain organs, less attention has been paid to actually building an atlas for organs other than the brain. Motivated by the automatic identification of normal organs for applications in radiation therapy treatment planning, we present a method to construct a probabilistic atl

Abstract Purpose: To develop a radiomics signature based on preoperative MRI to estimate disease-free survival (DFS) in patients with invasive breast cancer and to establish a radiomics nomogram that incorporates the radiomics signature and MRI and clinicopathological findings. Experimental Design: We identified 294 patients with invasive breast cancer who underwent preoperative MRI. Patients were randomly divided into training (n = 194) and validation (n = 100) sets. A radiomics signature (Rad-

BACKGROUND: In the natural environment, photodegradation is one of the most common degradative processes of pesticides. In order to reduce the photodegradation of pesticides, and so increase their killing activity against target pests, chitosan-coated beeswax solid lipid nanoparticles (CH-BSLNs) were prepared by a combination of hot homogenization and sonication, with deltamethrin as an active ingredient. RESULTS: Under optimal conditions, the highest encapsulation efficiency (95%) and a high pa

We have designed and evaluated coacervate microcapsules-immobilized multilayer sodium alginate beads (CMs-M-ALG-Beads) for oral drug delivery. The CMs-M-ALG-Beads were prepared by immobilization of doxorubicin hydrochloride (DOX) loaded chitosan/carboxymethyl coacervate microcapsules (DOX:CS/CMCS-CMs) in the core and layers of the multilayer sodium alginate beads. The obtained CMs-M-ALG-beads exhibited layer-by-layer structure and rough surface with many nanoscale particles. The swelling charact

Our data indicate that parametric PET/MRI using P(CHOL/ADC) improves lesion-to-background contrast (TBRs) of Gleason ≥ 3 + 4 disease, compared with (11)C-choline PET/CT or diffusion-weighted MRI, and thus hold promise that parametric imaging performed on hybrid PET/MRI may further improve identification and localization of significant primary prostate cancer.

Autism spectrum disorder (ASD) is a neurodevelopmental disability with global implication. Altered brain connectivity in the language network has frequently been reported in ASD patients using task-based functional magnetic resonance imaging (fMRI) compared to typically developing (TD) participants. Most of these studies have focused on a specific age group or mixed age groups with ASD. In the current study, we investigated age-related changes in functional connectivity related measure, degree c

The preprocessing of functional magnetic resonance imaging (fMRI) data is necessary to remove unwanted artifacts and transform the data into a standard format. There are several neuroimaging data processing tools that are widely used, such as SPM, AFNI, FSL, FreeSurfer, Workbench, and fMRIPrep. Different data preprocessing pipelines yield differing results, which might reduce the reproducibility of neuroimaging studies. Here, we developed a preprocessing pipeline for T1-weighted structural MRI a

The purpose of this study was to identify perfusional subregions sharing similar kinetic characteristics from dynamic contrast-enhanced magnetic resonance imaging (MRI) using data-driven clustering, and to evaluate the effect of perfusional heterogeneity based on those subregions on patients’ survival outcomes in various risk models. From two hospitals, 308 and 147 women with invasive breast cancer who underwent preoperative MRI between October 2011 and July 2012 were retrospectively enrolled as

Obesity causes critical health problems including diabetes and hypertension that affect billions of people worldwide. Obesity and eating behaviors are believed to be closely linked but their relationship through brain networks has not been fully explored. We identified functional brain networks associated with obesity and examined how the networks were related to eating behaviors. Resting state functional magnetic resonance imaging (MRI) scans were obtained for 82 participants. Data were from an

Classification of headache disorders is dependent on a subjective self-report from patients and its interpretation by physicians. We aimed to apply objective data-driven machine learning approaches to analyze patient-reported symptoms and test the feasibility of the automated classification of headache disorders. The self-report data of 2162 patients were analyzed. Headache disorders were merged into five major entities. The patients were divided into training (n = 1286) and test (n = 876) cohor