Artificial Intelligence Medical Compendium

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

Showing 46,541 to 46,550 of 224,199 articles

3D Modality-Aware Pre-training for Vision-Language Model in MRI Multi-organ Abnormality Detection

arXiv Feb 27, 2026
Vision-language models (VLMs) show strong potential for complex diagnostic tasks in medical imaging. However, applying VLMs to multi-organ medical imaging introduces two principal challenges: (1) modality-specific vision-language alignment and (2) cr... read more 
Computer Vision and Pattern Recognition cs.AI

Suppressing Prior-Comparison Hallucinations in Radiology Report Generation via Semantically Decoupled Latent Steering

arXiv Feb 27, 2026
Automated radiology report generation using vision-language models (VLMs) is limited by the risk of prior-comparison hallucination, where the model generates historical findings unsupported by the current study. We address this challenge with a train... read more 
Computer Vision and Pattern Recognition

Vision-Language Semantic Grounding for Multi-Domain Crop-Weed Segmentation

arXiv Feb 27, 2026
Fine-grained crop-weed segmentation is essential for enabling targeted herbicide application in precision agriculture. However, existing deep learning models struggle to generalize across heterogeneous agricultural environments due to reliance on dat... read more 
Computer Vision and Pattern Recognition

Towards Source-Aware Object Swapping with Initial Noise Perturbation

arXiv Feb 27, 2026
Object swapping aims to replace a source object in a scene with a reference object while preserving object fidelity, scene fidelity, and object-scene harmony. Existing methods either require per-object finetuning and slow inference or rely on extra p... read more 
Computer Vision and Pattern Recognition

Can Unified Generation and Understanding Models Maintain Semantic Equivalence Across Different Output Modalities?

arXiv Feb 27, 2026
Unified Multimodal Large Language Models (U-MLLMs) integrate understanding and generation within a single architecture. However, existing evaluations typically assess these capabilities separately, overlooking semantic equivalence, i.e., the ability ... read more 
Computer Vision and Pattern Recognition

StemVLA:An Open-Source Vision-Language-Action Model with Future 3D Spatial Geometry Knowledge and 4D Historical Representation

arXiv Feb 27, 2026
Vision-language-action (VLA) models integrate visual observations and language instructions to predict robot actions, demonstrating promising generalization in manipulation tasks. However, most existing approaches primarily rely on direct mappings fr... read more 
Robotics cs.CV

A Difference-in-Difference Approach to Detecting AI-Generated Images

arXiv Feb 27, 2026
Diffusion models are able to produce AI-generated images that are almost indistinguishable from real ones. This raises concerns about their potential misuse and poses substantial challenges for detecting them. Many existing detectors rely on reconstr... read more 
Computer Vision and Pattern Recognition

Unsupervised Causal Prototypical Networks for De-biased Interpretable Dermoscopy Diagnosis

arXiv Feb 27, 2026
Despite the success of deep learning in dermoscopy image analysis, its inherent black-box nature hinders clinical trust, motivating the use of prototypical networks for case-based visual transparency. However, inevitable selection bias in clinical da... read more 
Image and Video Processing cs.CV

Neural Image Space Tessellation

arXiv Feb 27, 2026
We present Neural Image-Space Tessellation (NIST), a lightweight screen-space post-processing approach that produces the visual effect of tessellated geometry while rendering only the original low-polygon meshes. Inspired by our observation from Phon... read more 
Graphics cs.CV

Learning Accurate Segmentation Purely from Self-Supervision

arXiv Feb 27, 2026
Accurately segmenting objects without any manual annotations remains one of the core challenges in computer vision. In this work, we introduce Selfment, a fully self-supervised framework that segments foreground objects directly from raw images witho... read more 
Computer Vision and Pattern Recognition
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