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Article
Early diagnosis and clinical score prediction of Parkinson's disease based on longitudinal neuroimaging data
Parkinson's disease (PD) is an irreversible neurodegenerative disease that has serious impacts on patients' lives. To provide timely accurate treatment and delay the deterioration of the disease, the accurate ...
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Chapter and Conference Paper
Acute Ischemic Stroke Onset Time Classification with Dynamic Convolution and Perfusion Maps Fusion
In treating acute ischemic stroke (AIS), determining the time since stroke onset (TSS) is crucial. Computed tomography perfusion (CTP) is vital for determining TSS by providing sufficient cerebral blood flow i...
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Chapter and Conference Paper
STAU-Net: A Spatial Structure Attention Network for 3D Coronary Artery Segmentation
Automated segmentation of coronary artery is critical yet challenging for the detection and quantification of cardiovascular diseases. Considering the limitation of computing power, most existing 3D coronary a...
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Chapter and Conference Paper
Dual-Branch Attention Network and Atrous Spatial Pyramid Pooling for Diabetic Retinopathy Classification Using Ultra-Widefield Images
Diabetic Retinopathy (DR) is a very common retinal disease in the world, which can affect vision and even cause blindness. Early diagnosis can effectively prevent the disease, or at least delay the progression...
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Chapter and Conference Paper
Weakly-Supervised Lesion-Aware and Consistency Regularization for Retinitis Pigmentosa Detection from Ultra-Widefield Images
Retinitis pigmentosa (RP) is one of the most common retinal diseases caused by gene defects, which can lead to night blindness or complete blindness. Accurate diagnosis and lesion identification are significan...
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Chapter and Conference Paper
Multi-level Light U-Net and Atrous Spatial Pyramid Pooling for Optic Disc Segmentation on Fundus Image
Optic disc (OD) is the main anatomical structures in retinal images. It is very important to conduct reliable OD segmentation in the automatic diagnosis of many fundus diseases. For OD segmentation, the previo...
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Chapter and Conference Paper
Template-Oriented Multi-task Sparse Low-Rank Learning for Parkinson’s Diseases Diagnosis
Parkinson’s disease (PD) is a long-term degenerative disorder of the central nervous system. Early diagnosis of PD has great clinical significance as patients would be able to receive specialized treatment ear...
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Article
Multipurpose watermarking scheme via intelligent method and chaotic map
In this paper, we propose a novel multipurpose intelligent image watermarking scheme for both content authentication and copyright protection. To achieve this, we first utilize integer discrete wavelet transfo...
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Chapter and Conference Paper
Diagnosis of Parkinson’s Disease in Genetic Cohort Patients via Stage-Wise Hierarchical Deep Polynomial Ensemble Learning
As a neurodegenerative disease, Parkinson’s disease (PD) has gradually become common in the elderly. Effective disease diagnosis has become increasingly important, especially in the patients with mutation of P...
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Chapter and Conference Paper
Predicting Early Stages of Neurodegenerative Diseases via Multi-task Low-Rank Feature Learning
Early stages of neurodegenerative diseases draw increasing recognition as obscure symptoms may appear before classical clinical diagnosis. For this reason, we propose a novel multi-task low-rank feature learni...
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Chapter and Conference Paper
Unsupervised Feature Selection via Adaptive Embedding and Sparse Learning for Parkinson’s Disease Diagnosis
Parkinson’s disease (PD) is known as a progressive neurodegenerative disease in elderly people. Apart from decelerating the disease exacerbation, early and accurate diagnosis also alleviates mental and physica...
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Chapter and Conference Paper
Multi-task Sparse Low-Rank Learning for Multi-classification of Parkinson’s Disease
Identifying prodromal stages of Parkinson’s disease (PD) draws increasing recognition as non-motor symptoms may appear before classical clinical diagnosis based on motor signs. To effectively develop a compute...
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Chapter and Conference Paper
Longitudinal and Multi-modal Data Learning via Joint Embedding and Sparse Regression for Parkinson’s Disease Diagnosis
Parkinson’s disease (PD) is a neurodegenerative progressive disease that mainly affects the motor systems of patients. To slow this disease deterioration, robust and accurate diagnosis of PD is an effective wa...
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Chapter and Conference Paper
ESD-WSN: An Efficient SDN-Based Wireless Sensor Network Architecture for IoT Applications
Wireless sensor networks (WSNs) are considered as a key enabler for the paradigm of Internet of Things (IoT). With increasing number of devices connected to the IoT environments, traditional solutions for WSNs...
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Article
Open AccessThe 5th International Conference on Biomedical Engineering and Biotechnology (ICBEB 2016)
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Chapter and Conference Paper
Hybrid SVD-Based Audio Watermarking Scheme
In this paper, a new blind Singular Value Decomposition (SVD) and quantization based audio watermarking scheme is proposed. The watermark information is meaningful binary image permuted by the Piecewise Affine...
