Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 57,471 to 57,480 of 227,388 articles

Feature Projection Learning for Better Vision-Language Reasoning

arXiv Jan 28, 2026
Vision-Language Pre-Trained models, notably CLIP, that utilize contrastive learning have proven highly adept at extracting generalizable visual features. To inherit the well-learned knowledge of VLP models for downstream tasks, several approaches aim... read more 
Computer Vision and Pattern Recognition

BLENDER: Blended Text Embeddings and Diffusion Residuals for Intra-Class Image Synthesis in Deep Metric Learning

arXiv Jan 28, 2026
The rise of Deep Generative Models (DGM) has enabled the generation of high-quality synthetic data. When used to augment authentic data in Deep Metric Learning (DML), these synthetic samples enhance intra-class diversity and improve the performance o... read more 
Computer Vision and Pattern Recognition

Reversible Efficient Diffusion for Image Fusion

arXiv Jan 28, 2026
Multi-modal image fusion aims to consolidate complementary information from diverse source images into a unified representation. The fused image is expected to preserve fine details and maintain high visual fidelity. While diffusion models have demon... read more 
Computer Vision and Pattern Recognition

StreamFusion: Scalable Sequence Parallelism for Distributed Inference of Diffusion Transformers on GPUs

arXiv Jan 28, 2026
Diffusion Transformers (DiTs) have gained increasing adoption in high-quality image and video generation. As demand for higher-resolution images and longer videos increases, single-GPU inference becomes inefficient due to increased latency and large ... read more 
Distributed, Parallel, and Cluster Computing cs.CV

A Source-Free Approach for Domain Adaptation via Multiview Image Transformation and Latent Space Consistency

arXiv Jan 28, 2026
Domain adaptation (DA) addresses the challenge of transferring knowledge from a source domain to a target domain where image data distributions may differ. Existing DA methods often require access to source domain data, adversarial training, or compl... read more 
Computer Vision and Pattern Recognition

A Learning-based Framework for Spatial Impulse Response Compensation in 3D Photoacoustic Computed Tomography

arXiv Jan 28, 2026
Photoacoustic computed tomography (PACT) is a promising imaging modality that combines the advantages of optical contrast with ultrasound detection. Utilizing ultrasound transducers with larger surface areas can improve detection sensitivity. However... read more 
Machine Learning eess.SP physics.med-ph

Bridging the Applicator Gap with Data-Doping:Dual-Domain Learning for Precise Bladder Segmentation in CT-Guided Brachytherapy

arXiv Jan 28, 2026
Performance degradation due to covariate shift remains a major challenge for deep learning models in medical image segmentation. An open question is whether samples from a shifted distribution can effectively support learning when combined with limit... read more 
Computer Vision and Pattern Recognition

Physically Guided Visual Mass Estimation from a Single RGB Image

arXiv Jan 28, 2026
Estimating object mass from visual input is challenging because mass depends jointly on geometric volume and material-dependent density, neither of which is directly observable from RGB appearance. Consequently, mass prediction from pixels is ill-pos... read more 
Computer Vision and Pattern Recognition cs.AI

Structure-constrained Language-informed Diffusion Model for Unpaired Low-dose Computed Tomography Angiography Reconstruction

arXiv Jan 28, 2026
The application of iodinated contrast media (ICM) improves the sensitivity and specificity of computed tomography (CT) for a wide range of clinical indications. However, overdose of ICM can cause problems such as kidney damage and life-threatening al... read more 
Computer Vision and Pattern Recognition cs.AI

TPGDiff: Hierarchical Triple-Prior Guided Diffusion for Image Restoration

arXiv Jan 28, 2026
All-in-one image restoration aims to address diverse degradation types using a single unified model. Existing methods typically rely on degradation priors to guide restoration, yet often struggle to reconstruct content in severely degraded regions. A... read more 
Computer Vision and Pattern Recognition
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