{ "item_title" : "Graph Learning in Medical Imaging", "item_author" : [" Daoqiang Zhang", "Luping Zhou", "Biao Jie "], "item_description" : "Graph Hyperalignment for Multi-Subject fMRI Functional Alignment.- Interactive 3D Segmentation Editing and Refinement via Gated Graph Neural Networks.- Adaptive Thresholding of Functional Connectivity Networks for fMRI-based Brain Disease Analysis.- Graph-kernel-based Multi-task Structured Feature Selection on Multi-level Functional Connectivity Networks for Brain Disease Classification.- Linking convolutional neural networks with graph convolutional networks: application in pulmonary artery-vein separation.- Comparative Analysis of Magnetic Resonance Fingerprinting Dictionaries via Dimensionality Reduction.- Learning Deformable Point Set Registration with Regularized Dynamic Graph CNNs for Large Lung Motion in COPD Patients.- Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography.- Triplet Graph Convolutional Network forMulti-scale Analysis of Functional Connectivityusing Functional MRI.- Multi-Scale Graph Convolutional Network for Mild Cognitive Impairment Detection.- DeepBundle: Fiber Bundle Parcellation With Graph CNNs.- Identification of Functional Connectivity Features in Depression Subtypes Using a Data-Driven Approach.- Movie-watching fMRI Reveals Inter-subject Synchrony Alteration in Functional Brain Activity in ADHD.- Weakly- and Semi- Supervised Graph CNN for identifying Basal Cell Carcinoma on Pathological images.- Geometric Brain Surface Network For Brain Cortical Parcellation.- Automatic Detection of Craniomaxillofacial Anatomical Landmarks on CBCT Images using 3D Mask R-CNN.- Discriminative-Region-Aware Residual Network for Adolescent Brain Structure and Cognitive Development Analysis.- Graph Modeling for Identifying Breast Tumor Located in Dense Background of a Mammogram.- OCD Diagnosis via Smoothing Sparse Network and Stacked Sparse Auto-Encoder Learning.- A Longitudinal MRI Study of Amygdala and Hippocampal Subfields for Infants with Risk of Autism.- CNS: CycleGAN-assisted Neonatal Segmentation Model for Cross-Datasets.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/3/03/035/816/303035816X_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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