30 Result(s)
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Article
Open AccessDevelopment and application of Chinese medical ontology for diabetes mellitus
To develop a Chinese Diabetes Mellitus Ontology (CDMO) and explore methods for constructing high-quality Chinese biomedical ontologies.
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Article
Open AccessClassifying the lifestyle status for Alzheimer’s disease from clinical notes using deep learning with weak supervision
Since no effective therapies exist for Alzheimer’s disease (AD), prevention has become more critical through lifestyle status changes and interventions. Analyzing electronic health records (EHRs) of patients w...
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Article
Open AccessAutomatic breast lesion segmentation in phase preserved DCE-MRIs
We offer a framework for automatically and accurately segmenting breast lesions from Dynamic Contrast Enhanced (DCE) MRI in this paper. The framework is built using max flow and min cut problems in the continu...
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Article
Open AccessInfluencing factors of physicians’ prescription behavior in selecting essential medicines: a cross-sectional survey in Chinese county hospitals
To explore the key factors affecting prescription practices of essential medicines in Chinese county hospital. National essential medicine policy (NEMP) plays important roles in health care system, especially ...
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Chapter and Conference Paper
Joint Craniomaxillofacial Bone Segmentation and Landmark Digitization by Context-Guided Fully Convolutional Networks
Generating accurate 3D models from cone-beam computed tomography (CBCT) images is an important step in develo** treatment plans for patients with craniomaxillofacial (CMF) deformities. This process often inv...
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Chapter and Conference Paper
Feature Selection Based on Iterative Canonical Correlation Analysis for Automatic Diagnosis of Parkinson’s Disease
Parkinson’s disease (PD) is a major progressive neurodegenerative disorder. Accurate diagnosis of PD is crucial to control the symptoms appropriately. However, its clinical diagnosis mostly relies on the subje...
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Chapter and Conference Paper
Two-Stage Simulation Method to Improve Facial Soft Tissue Prediction Accuracy for Orthognathic Surgery
It is clinically important to accurately predict facial soft tissue changes prior to orthognathic surgery. However, the current simulation methods are problematic, especially in clinically critical regions. We...
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Chapter and Conference Paper
Tight Graph Framelets for Sparse Diffusion MRI q-Space Representation
In diffusion MRI, the outcome of estimation problems can often be improved by taking into account the correlation of diffusion-weighted images scanned with neighboring wavevectors in q-space. For this purpose, we...
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Chapter and Conference Paper
Correlation-Weighted Sparse Group Representation for Brain Network Construction in MCI Classification
Analysis of brain functional connectivity network (BFCN) has shown great potential in understanding brain functions and identifying biomarkers for neurological and psychiatric disorders, such as Alzheimer’s di...
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Chapter and Conference Paper
Reveal Consistent Spatial-Temporal Patterns from Dynamic Functional Connectivity for Autism Spectrum Disorder Identification
Functional magnetic resonance imaging (fMRI) provides a non-invasive way to investigate brain activity. Recently, convergent evidence shows that the correlations of spontaneous fluctuations between two distinc...
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Chapter and Conference Paper
Automated Three-Piece Digital Dental Articulation
In craniomaxillofacial (CMF) surgery, a critical step is to reestablish dental occlusion. Digitally establishing new dental occlusion is extremely difficult. It is especially true when the maxilla is segmental...
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Chapter and Conference Paper
Iterative Subspace Screening for Rapid Sparse Estimation of Brain Tissue Microstructural Properties
Diffusion magnetic resonance imaging (DMRI) is a powerful imaging modality due to its unique ability to extract microstructural information by utilizing restricted diffusion to probe compartments that are much...
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Chapter and Conference Paper
Diffusion Compartmentalization Using Response Function Groups with Cardinality Penalization
Spherical deconvolution (SD) of the white matter (WM) diffusion-attenuated signal with a fiber signal response function has been shown to yield high-quality estimates of fiber orientation distribution function...
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Chapter and Conference Paper
Brain Tissue Segmentation Based on Diffusion MRI Using ℓ0 Sparse-Group Representation Classification
We present a method for automated brain tissue segmentation based on diffusion MRI. This provides information that is complementary to structural MRI and facilitates fusion of information between the two imagi...
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Chapter and Conference Paper
Space-Frequency Detail-Preserving Construction of Neonatal Brain Atlases
Brain atlases are an integral component of neuroimaging studies. However, most brain atlases are fuzzy and lack structural details, especially in the cortical regions. In particular, neonatal brain atlases are...
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Chapter and Conference Paper
Automatic Craniomaxillofacial Landmark Digitization via Segmentation-Guided Partially-Joint Regression Forest Model
Craniomaxillofacial (CMF) deformities involve congenital and acquired deformities of the head and face. Landmark digitization is a critical step in quantifying CMF deformities. In current clinical practice, CM...
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Chapter and Conference Paper
Brain Connectivity Hyper-Network for MCI Classification
Brain connectivity network has been used for diagnosis and classification of neurodegenerative diseases, such as Alzheimer’s disease (AD) as well as its early stage, i.e., mild cognitive impairment (MCI). Howe...
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Chapter and Conference Paper
Deep Learning Based Imaging Data Completion for Improved Brain Disease Diagnosis
Combining multi-modality brain data for disease diagnosis commonly leads to improved performance. A challenge in using multi-modality data is that the data are commonly incomplete; namely, some modality might ...
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Chapter and Conference Paper
Large Deformation Diffeomorphic Registration of Diffusion-Weighted Images with Explicit Orientation Optimization
We seek to compute a diffeomorphic map between a pair of diffusion-weighted images under large deformation. Unlike existing techniques, our method allows any diffusion model to be fitted after registration for su...
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Chapter and Conference Paper
Manifold Regularized Multi-Task Feature Selection for Multi-Modality Classification in Alzheimer’s Disease
Accurate diagnosis of Alzheimer’s disease (AD), as well as its prodromal stage (i.e., mild cognitive impairment, MCI), is very important for possible delay and early treatment of the disease. Recently, multi-m...
