AIMC Topic: Image Processing, Computer-Assisted

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Masked Deformation Modeling for Volumetric Brain MRI Self-Supervised Pre-Training.

IEEE transactions on medical imaging Mar 17, 2025
Self-supervised learning (SSL) has been proposed to alleviate neural networks' reliance on annotated data and to improve downstream tasks' performance, which has obtained substantial success in several volumetric medical image segmentation tasks. How...
Supervised Machine Learning Brain Humans Neuroimaging Female Algorithms Male Adult Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Deep Learning for High Speed Optical Coherence Elastography With a Fiber Scanning Endoscope.

IEEE transactions on medical imaging Mar 17, 2025
Tissue stiffness is related to soft tissue pathologies and can be assessed through palpation or via clinical imaging systems, e.g., ultrasound or magnetic resonance imaging. Typically, the image based approaches are not suitable during interventions,...
Phantoms, Imaging Endoscopes Elasticity Imaging Techniques Deep Learning Image Processing, Computer-Assisted Equipment Design Animals Swine Humans
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CGNet: A Correlation-Guided Registration Network for Unsupervised Deformable Image Registration.

IEEE transactions on medical imaging Mar 17, 2025
Deformable medical image registration plays a significant role in medical image analysis. With the advancement of deep neural networks, learning-based deformable registration methods have made great strides due to their ability to perform fast end-to...
Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Unsupervised Machine Learning Neural Networks, Computer Algorithms Databases, Factual Brain
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UC-NeRF: Uncertainty-Aware Conditional Neural Radiance Fields From Endoscopic Sparse Views.

IEEE transactions on medical imaging Mar 17, 2025
Visualizing surgical scenes is crucial for revealing internal anatomical structures during minimally invasive procedures. Novel View Synthesis is a vital technique that offers geometry and appearance reconstruction, enhancing understanding, planning,...
Uncertainty Humans Neural Networks, Computer Algorithms Endoscopy Imaging, Three-Dimensional Image Processing, Computer-Assisted
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A Learnable Prior Improves Inverse Tumor Growth Modeling.

IEEE transactions on medical imaging Mar 17, 2025
Biophysical modeling, particularly involving partial differential equations (PDEs), offers significant potential for tailoring disease treatment protocols to individual patients. However, the inverse problem-solving aspect of these models presents a ...
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Models, Biological Algorithms Brain Brain Neoplasms Humans
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Effective Semi-Supervised Medical Image Segmentation With Probabilistic Representations and Prototype Learning.

IEEE transactions on medical imaging Mar 17, 2025
Label scarcity, class imbalance and data uncertainty are three primary challenges that are commonly encountered in the semi-supervised medical image segmentation. In this work, we focus on the data uncertainty issue that is overlooked by previous lit...
Models, Statistical Diagnostic Imaging Supervised Machine Learning Algorithms Image Processing, Computer-Assisted Humans
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DPI-MoCo: Deep Prior Image Constrained Motion Compensation Reconstruction for 4D CBCT.

IEEE transactions on medical imaging Mar 17, 2025
4D cone-beam computed tomography (CBCT) plays a critical role in adaptive radiation therapy for lung cancer. However, extremely sparse sampling projection data will cause severe streak artifacts in 4D CBCT images. Existing deep learning (DL) methods ...
Deep Learning Cone-Beam Computed Tomography Image Processing, Computer-Assisted Humans Algorithms Lung Phantoms, Imaging Four-Dimensional Computed Tomography Lung Neoplasms Artifacts
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FedLPPA: Learning Personalized Prompt and Aggregation for Federated Weakly-Supervised Medical Image Segmentation.

IEEE transactions on medical imaging Mar 17, 2025
Federated learning (FL) effectively mitigates the data silo challenge brought about by policies and privacy concerns, implicitly harnessing more data for deep model training. However, traditional centralized FL models grapple with diverse multi-cente...
Algorithms Supervised Machine Learning Deep Learning Image Processing, Computer-Assisted Humans
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Fully automatic categorical analysis of striatal subregions in dopamine transporter SPECT using a convolutional neural network.

Annals of nuclear medicine Mar 16, 2025
OBJECTIVE: To provide fully automatic scanner-independent 5-level categorization of the [I]FP-CIT uptake in striatal subregions in dopamine transporter SPECT.
Male Middle Aged Convolutional Neural Networks Aged Adult Tomography, Emission-Computed, Single-Photon Image Processing, Computer-Assisted Tropanes Automation Humans Dopamine Plasma Membrane Transport Proteins Corpus Striatum Female
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Light scattering imaging modal expansion cytometry for label-free single-cell analysis with deep learning.

Computer methods and programs in biomedicine Mar 15, 2025
BACKGROUND AND OBJECTIVE: Single-cell imaging plays a key role in various fields, including drug development, disease diagnosis, and personalized medicine. To obtain multi-modal information from a single-cell image, especially for label-free cells, t...
Cell Line, Tumor Single-Cell Analysis Female Image Processing, Computer-Assisted Humans Light Uterine Cervical Neoplasms Algorithms Scattering, Radiation Deep Learning
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