AIMC Journal:
IEEE transactions on medical imaging
Showing 641 to 650 of 699 articles
Transfer learning improves supervised image segmentation across imaging protocols.
IEEE transactions on medical imaging
Nov 4, 2014
The variation between images obtained with different scanners or different imaging protocols presents a major challenge in automatic segmentation of biomedical images. This variation especially hampers the application of otherwise successful supervis...
Cross- and Intra-Image Prototypical Learning for Multi-Label Disease Diagnosis and Interpretation.
IEEE transactions on medical imaging
Jun 1, 2025
Recent advances in prototypical learning have shown remarkable potential to provide useful decision interpretations associating activation maps and predictions with class-specific training prototypes. Such prototypical learning has been well-studied ...
GVM-Net: A GNN-Based Vessel Matching Network for 2D/3D Non-Rigid Coronary Artery Registration.
IEEE transactions on medical imaging
Jun 1, 2025
The registration of coronary artery structures from preoperative coronary computed tomography angiography to intraoperative coronary angiography is of great interest to improve guidance in percutaneous coronary interventions. However, non-rigid defor...
Ultra-Sparse-View Cone-Beam CT Reconstruction-Based Strictly Structure-Preserved Deep Neural Network in Image-Guided Radiation Therapy.
IEEE transactions on medical imaging
Jun 1, 2025
Radiation therapy is regarded as the mainstay treatment for cancer in clinic. Kilovoltage cone-beam CT (CBCT) images have been acquired for most treatment sites as the clinical routine for image-guided radiation therapy (IGRT). However, repeated CBCT...
GDP-Net: Global Dependency-Enhanced Dual-Domain Parallel Network for Ring Artifact Removal.
IEEE transactions on medical imaging
Jun 1, 2025
In Computed Tomography (CT) imaging, the ring artifacts caused by the inconsistent detector response can significantly degrade the reconstructed images, having negative impacts on the subsequent applications. The new generation of CT systems based on...
Information Geometric Approaches for Patient-Specific Test-Time Adaptation of Deep Learning Models for Semantic Segmentation.
IEEE transactions on medical imaging
Jun 1, 2025
The test-time adaptation (TTA) of deep-learning-based semantic segmentation models, specific to individual patient data, was addressed in this study. The existing TTA methods in medical imaging are often unconstrained, require anatomical prior inform...
Exploring Unbiased Activation Maps for Weakly Supervised Tissue Segmentation of Histopathological Images.
IEEE transactions on medical imaging
Jun 1, 2025
Tissue segmentation in histopathological images plays a crucial role in computational pathology, owing to its significant potential to indicate the prognosis of cancer patients. Presently, numerous Weakly Supervised Semantic Segmentation (WSSS) metho...
Enhancing Medical Vision-Language Contrastive Learning via Inter-Matching Relation Modeling.
IEEE transactions on medical imaging
Jun 1, 2025
Medical image representations can be learned through medical vision-language contrastive learning (mVLCL) where medical imaging reports are used as weak supervision through image-text alignment. These learned image representations can be transferred ...
Cardiac Phase Estimation Using Deep Learning Analysis of Pulsed-Mode Projections: Toward Autonomous Cardiac CT Imaging.
IEEE transactions on medical imaging
Jun 1, 2025
Cardiac CT plays an important role in diagnosing heart diseases but is conventionally limited by its complex workflow that requires dedicated phase and bolus tracking devices [e.g., electrocardiogram (ECG) gating]. This work reports first progress to...
Score-Based Diffusion Models With Self-Supervised Learning for Accelerated 3D Multi-Contrast Cardiac MR Imaging.
IEEE transactions on medical imaging
Jun 1, 2025
Long scan time significantly hinders the widespread applications of three-dimensional multi-contrast cardiac magnetic resonance (3D-MC-CMR) imaging. This study aims to accelerate 3D-MC-CMR acquisition by a novel method based on score-based diffusion ...
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