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IEEE Journal of Biomedical and Health Informatics

Siqi Li, Huiyan Jiang, Yu-Dong Yao, Benqiang Yang
Organ segmentation on computed tomography (CT) images is of great importance in medical diagnoses and treatment. This paper proposes organ location determination and contour sparse representation methods (OLD-CSR) for multiorgan segmentation (liver, kidney, and spleen) on abdomen CT images using an extreme learning machine (ELM) classifier. First, a location determination method is designed to obtain location information of each organ, which is used for coarse segmentation. Second, for coarse-to-fine segmentation, a contour gradient and rate change based feature point extraction method is proposed...
May 17, 2017: IEEE Journal of Biomedical and Health Informatics
Alok Chowdhury, Dian Tjondronegoro, Vinod Chandran, Stewart Trost
This paper proposes the use of posterior-adapted class-based weighted decision fusion to effectively combine multiple accelerometers data for improving physical activity recognition. The cutting-edge performance of this method is benchmarked against model-based weighted fusion and class-based weighted fusion without posterior adaptation, based on two publicly available datasets, namely PAMAP2 and MHEALTH. Experimental results show that: (a) posterior-adapted class-based weighted fusion outperformed model-based and class-based weighted fusion; (b) decision fusion with two accelerometers showed statistically significant improvement in average performance compared to the use of a single accelerometer;...
May 17, 2017: IEEE Journal of Biomedical and Health Informatics
Zhen Yu, Ee-Leng Tan, Dong Ni, Jing Qin, Siping Chen, Shenli Li, Baiying Lei, Tianfu Wang
Ultrasound imaging has become a prevalent examination method in prenatal diagnosis. Accurate acquisition of fetal facial standard plane (FFSP) is the most important precondition for subsequent diagnosis and measurement. In the past few years, considerable effort has been devoted to FFSP recognition using various hand-crafted features, but the recognition performance is still unsatisfactory due to the high intra-class variation of FFSPs and the high degree of visual similarity between FFSPs and other non-FFSPs...
May 17, 2017: IEEE Journal of Biomedical and Health Informatics
Suvra Pal, N Balakrishnan
In this paper, we develop likelihood inference based on the expectation maximization (EM) algorithm for the Box- Cox transformation cure rate model assuming the lifetimes to follow a Weibull distribution. A simulation study is carried out to demonstrate the performance of the proposed estimation method. Through Monte Carlo simulations, we also study the effect of model mis-specification on the estimate of cure rate. Finally, we analyze a well-known data on melanoma with the model and the inferential method developed here...
May 16, 2017: IEEE Journal of Biomedical and Health Informatics
Jun Zhang, Mingxia Liu, Le An, Yaozong Gao, Dinggang Shen
Structural magnetic resonance imaging (MRI) has been proven to be an effective tool for Alzheimer's disease (AD) diagnosis. While conventional MRI-based AD diagnosis typically uses images acquired at a single time point, a longitudinal study is more sensitive in detecting early pathological changes of AD, making it more favorable for accurate diagnosis. In general, there are two challenges faced in MRI-based diagnosis. First, extracting features from structural MR images requires timeconsuming nonlinear registration and tissue segmentation, whereas the longitudinal study with involvement of more scans further exacerbates the computational costs...
May 16, 2017: IEEE Journal of Biomedical and Health Informatics
Paul Nickerson, Raheleh Baharloo, Amal A Wanigatunga, Todd D Manini, Patrick J Tighe, Parisa Rashidi
The modern healthcare landscape has seen the rapid emergence of techniques and devices which temporally monitor and record physiological signals. The prevalence of time series data within the healthcare field necessitates the development of methods which can analyze the data in order to draw meaningful conclusions. Time series behavior is notoriously difficult to intuitively understand due to its intrinsic high-dimensionality, which is compounded in the case of analyzing groups of time series collected from different patients...
May 16, 2017: IEEE Journal of Biomedical and Health Informatics
Sidra Minhas, Aasia Khanum, Farhan Riaz, Shoab Khan, Atif Alvi
Mild Cognitive Impairment is a preclinical stage of Alzheimer's disease (AD). For effective treatment of AD, it is important to identify MCI patients who are at a high risk of developing AD over the course of time. İn this study, autoregressive modelling of multiple heterogeneous predictors of Alzheimer's dısease is performed to capture their evolution over time. The models are trained using three different arrangements of longitudinal data. These models are then used to estimate future biomarker readings of individual test subjects...
May 16, 2017: IEEE Journal of Biomedical and Health Informatics
Shuxia Zhu, Fei Shi, Dehui Xiang, Weifang Zhu, Haoyu Chen, Xinjian Chen
Choroid neovascularization (CNV) is caused by new blood vessels growing in the choroid and penetrating the Bruch membrane. It is the major cause of vision disability in many retinal diseases. Though anti-vascular endothelial growth factor (VEGF) injection has proved to be effective for treating CNV, treatment planning is essential to ensure the efficacy while reducing the risk. For this purpose, we propose a CNV growth model based on longitudinal Optical Coherence Tomography (OCT) images. The reaction-diffusion model is applied to simulate the growth and shrinkage of CNV volumes, and is solved by using finite element method (FEM)...
May 16, 2017: IEEE Journal of Biomedical and Health Informatics
Chaoyang Shi, Xiongbiao Luo, Jin Guo, Zoran Najdovski, Toshio Fukuda, Hongliang Ren
Intravascular ultrasound (IVUS) imaging provides two-dimensional (2D) real-time luminal and transmural cross-sectional images of intravascular vessels with detailed pathological information. It has offered significant advantages in terms of diagnosis and guidance and has been increasingly introduced from coronary interventions into more generalized endovascular surgery. However, IVUS itself does not provide spatial pose information for its generated images, making it difficult to construct a 3D intravascular visualization...
May 12, 2017: IEEE Journal of Biomedical and Health Informatics
Jing Li, Yi Wang, Baiying Lei, Jie-Zhi Cheng, Jing Qin, Tianfu Wang, Shenli Li, Dong Ni
Head circumference (HC) is one of the most important biometrics in assessing fetal growth during prenatal ultrasound examinations. However, the manual measurement of this biometric by doctors often requires substantial experience. We developed a learning-based framework that used prior knowledge and employed a fast ellipse fitting method (ElliFit) to measure HC automatically. We first integrated the prior knowledge about the gestational age and ultrasound scanning depth into a random forest classifier to localize the fetal head...
May 12, 2017: IEEE Journal of Biomedical and Health Informatics
Sina Khanmohammadi, Chun-An Chou
Epilepsy is one of the most common neurological disorders in the world. Prompt detection of seizure onset from electroencephalogram (EEG) signals can improve the treatment of epileptic patients. This paper presents a new adaptive patientspecific seizure onset detection framework that dynamically selects a feature from enhanced EEG signals to discriminate seizures from normal brain activity. The proposed framework employs principle component analysis (PCA) and common spatial patterns (CSP) to enhance the EEG signals and uses the extracted discriminative feature as an input for adaptive distance-based change point detector to identify the seizure onsets...
May 12, 2017: IEEE Journal of Biomedical and Health Informatics
Liehang Shi, Jianyong Sun, Yuanyuan Yang, Tonghui Ling, Mingqing Wang, Yiping Gu, Zhiming Yang, Yanqing Hua, Jianguo Zhang
OBJECTIVE: An innovative concept and method is introduced to use a three Dimensional (3D) anatomical graphic pattern called Visual Patient (VP) visually to index, represent and render the medical diagnostic records (MDRs) of a patient, so that a doctor can quickly learn the current and historical medical status of the patient by manipulating VP. The MDRs can be imaging diagnostic reports and DICOM images, laboratory reports and clinical summaries which can have clinical information relating to medical status of human organs or body parts...
May 8, 2017: IEEE Journal of Biomedical and Health Informatics
Ting Zhu, Li Luo, Xinli Zhang, Wenwu Shen
Variability and unpredictability are typical features of emergency departments (EDs) where patients randomly arrive with diverse conditions. Patient length of stay (LOS) represents the consumption level of hospital resources, and it is positively skewed and heterogeneous. Both accurate modeling of patient ED LOS and analysis of potential blocking causes are especially useful for patient scheduling and resource management. To tackle the uncertainty of ED LOS, this research introduces two methods: statistical modeling and distribution fitting...
May 5, 2017: IEEE Journal of Biomedical and Health Informatics
Bor-Shyh Lin, Pei-Jung Wu, Chien-Yu Chen
Recently, 2D/3D switchable displays have become the mainstream in 3D display technologies, and people can now watch 3D movies with a naked 2D/3D switchable display at home. However, some studies have indicated that people might encounter visual fatigue after enjoying a 3D film in the theater. Although 2D/3D switchable technologies have been widely developed, 3D display technologies are still lacking in ergonomic and human-care factors such as reducing visual fatigue. This study proposes a novel 2D/3D display auto-adjustment switch system to provide biofeedback functions to reduce users' visual fatigue...
May 3, 2017: IEEE Journal of Biomedical and Health Informatics
John Qiu, Hong-Jun Yoon, Paul A Fearn, Georgia D Tourassi
for cancer registries which process high volumes of free-text reports annually. Information extraction and coding is a manual, labor-intensive process. In this study we investigated deep learning and a convolutional neural network (CNN), for extracting ICDO- 3 topographic codes from a corpus of breast and lung cancer pathology reports. We performed two experiments, using a CNN and a more conventional term frequency vector approach, to assess the effects of class prevalence and inter-class transfer learning...
May 3, 2017: IEEE Journal of Biomedical and Health Informatics
Hyun-Gyu Lee, Sang-Chul Lee
We identify cells in microscopy images with stained nuclei, using the following process: candidate seeds for nuclei are identified as extrema in a Laplacian-of-Gaussian space, and weak candidates are eliminated from clusters obtained by ellipse fitting; a region of interest for each nucleus is then defined by combining local and global thresholding; and these regions are repeatedly merged and split by modeling the shape of a nucleus and measuring the roughness of the shared boundaries connected nuclei. This method showed superior abilities to detect the nucleus regions and to split the boundaries of connected nuclei...
May 2, 2017: IEEE Journal of Biomedical and Health Informatics
Fen Miao, Nan Fu, Yuan-Ting Zhang, Xiao-Rong Ding, Xi Hong, Qingyun He, Ye Li
Continuous blood pressure (BP) estimation using pulse transit time (PTT) is a promising method for unobtrusive BP measurement. However, the accuracy of this approach must be improved for it to be viable for a wide range of applications. This study proposes a novel continuous BP estimation approach that combines data mining techniques with a traditional mechanism-driven model. First, 14 features derived from simultaneous electrocardiogram and photoplethysmogram signals were extracted for beat-to-beat BP estimation...
April 28, 2017: IEEE Journal of Biomedical and Health Informatics
Rui Zhang, Oliver Amft
We propose to 3D-print personal fitted, regular-look smart eyeglasses frames equipped with bilateral Electromyography (EMG) recording to monitor Temporalis muscles' activity for automatic dietary monitoring. Personal fitting supported electrode-skin contact at temple ear bend and temple end positions. We evaluated the smart monitoring eyeglasses during in-lab and free-living studies of food chewing and eating event detection with ten participants. The in-lab study was designed to explore three natural food hardness levels and determine parameters of an energy-based chewing cycle detection...
April 27, 2017: IEEE Journal of Biomedical and Health Informatics
Ting Yu Liu, Kuan Jen Lin, Hsi-Chun Wu
Electrocardiogram (ECG) monitoring systems are widely used in healthcare. ECG data must be compressed for transmission and storage. Furthermore, there is a need to be able to directly process biomedical signals in encrypted domains to ensure the protection of patients' privacy. Existing encryption-then-compression (ETC) approaches for multimedia using the state-of-the-art encryption techniques inevitably sacrifice the compression efficiency or signal quality. This paper presents the first ETC approach for processing ECG data...
April 27, 2017: IEEE Journal of Biomedical and Health Informatics
Krishan Lal Khatri, Lakshman Tamil
Chronic Respiratory diseases, mainly asthma and Chronic Obstructive Pulmonary Disease (COPD), affect the lives of people by limiting their activities in various aspects. Overcrowding of hospital emergency departments (EDs) due to respiratory diseases in certain weather and environmental pollution conditions results in the degradation of quality of medical care, and even limits its availability. A useful tool for ED managers would be to forecast peak demand days so that they can take steps to improve the availability of medical care...
April 26, 2017: IEEE Journal of Biomedical and Health Informatics
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