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Organ-level instance segmentation enables continuous time-space-spectrum analysis of pre-clinical abdominal photoacoustic tomography images
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Contrastive machine learning reveals species -shared and -specific brain functional architecture
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Dual-modality visual feature flow for medical report generation
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AutoFOX: An automated cross-modal 3D fusion framework of coronary X-ray angiography and OCT
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Improving cross-domain generalizability of medical image segmentation using uncertainty and shape-aware continual test-time domain adaptation
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Personalized predictions of Glioblastoma infiltration: Mathematical models, Physics-Informed Neural Networks and multimodal scans
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DDoCT: Morphology preserved dual-domain joint optimization for fast sparse-view low-dose CT imaging
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Personalized dental crown design: A point-to-mesh completion network
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Brain networks and intelligence: A graph neural network based approach to resting state fMRI data
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SurgiTrack: Fine-grained multi-class multi-tool tracking in surgical videos
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Biomechanical modeling combined with pressure-volume loop analysis to aid surgical planning in patients with complex congenital heart disease
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Learnable color space conversion and fusion for stain normalization in pathology images
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2D echocardiography video to 3D heart shape reconstruction for clinical application
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Incorporating spatial information in deep learning parameter estimation with application to the intravoxel incoherent motion model in diffusion-weighted MRI
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SegRap2023: A benchmark of organs-at-risk and gross tumor volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma
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IVIM-Morph: Motion-compensated quantitative Intra-voxel Incoherent Motion (IVIM) analysis for functional fetal lung maturity assessment from diffusion-weighted MRI data
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Style mixup enhanced disentanglement learning for unsupervised domain adaptation in medical image segmentation
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Cross-center Model Adaptive Tooth segmentation
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Cooperative multi-task learning and interpretable image biomarkers for glioma grading and molecular subtyping
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Strategies for generating synthetic computed tomography-like imaging from radiographs: A scoping review
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Modeling annotator preference and stochastic annotation error for medical image segmentation
Modeling annotator preference and stochastic annotation error for medical image segmentation
Medical image segmentation plays a crucial role in delivering effective patient care in diagnostic and treatment practices...
Beam-wise dose composition learning for head and neck cancer dose prediction in radiotherapy
Beam-wise dose composition learning for head and neck cancer dose prediction in radiotherapy
Head and neck (H&N) cancer is a broad category of diverse cancer types, originating from various soft tissue, glands, ...
Multi-source multi-modal markers for Bayesian Networks: Application to the extremely preterm born brain
Multi-source multi-modal markers for Bayesian Networks: Application to the extremely preterm born brain
The preterm phenotype results from the interplay of multiple disorders affecting the brain and cognitive outcomes. Accurat...
Deep learning based synthesis of MRI, CT and PET: Review and analysis
Deep learning based synthesis of MRI, CT and PET: Review and analysis
Medical image synthesis represents a critical area of research in clinical decision-making, aiming to overcome the challen...
Synthesis-based imaging-differentiation representation learning for multi-sequence 3D/4D MRI
Synthesis-based imaging-differentiation representation learning for multi-sequence 3D/4D MRI
Multi-sequence MRIs show different characteristics of protons within tissues, resulting in various image appearances of wa...
FiCRoN, a deep learning-based algorithm for the automatic determination of intracellular parasite burden from fluorescence microscopy images
FiCRoN, a deep learning-based algorithm for the automatic determination of intracellular parasite burden from fluorescence microscopy images
Intracellular protozoan parasites are responsible for dramatic infectious diseases such as malaria, leishmaniasis, Chagas ...
Riemannian frameworks for the harmonization of resting-state functional MRI scans
Riemannian frameworks for the harmonization of resting-state functional MRI scans
Magnetic Resonance Imaging provides unprecedented images of the brain. Unfortunately, scanners and acquisition protocols c...
Automatic registration with continuous pose updates for marker-less surgical navigation in spine surgery
Automatic registration with continuous pose updates for marker-less surgical navigation in spine surgery
Established surgical navigation systems for pedicle screw placement have been proven to be accurate, but still reveal limi...
CartiMorph: A framework for automated knee articular cartilage morphometrics
CartiMorph: A framework for automated knee articular cartilage morphometrics
Knee articular cartilage morphometrics is an effective tool to derive imaging biomarkers for knee osteoarthritis (OA) (Gra...
A knowledge-interpretable multi-task learning framework for automated thyroid nodule diagnosis in ultrasound videos
A knowledge-interpretable multi-task learning framework for automated thyroid nodule diagnosis in ultrasound videos
Thyroid nodules, one of the most common diseases in the thyroid gland, pose a significant public health risk. Medical imag...
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