Artificial Intelligence Medical Compendium

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

Showing 62,171 to 62,180 of 230,319 articles

TrackletGPT: A Language-like GPT Framework for White Matter Tract Segmentation

arXiv Jan 20, 2026
White Matter Tract Segmentation is imperative for studying brain structural connectivity, neurological disorders and neurosurgery. This task remains complex, as tracts differ among themselves, across subjects and conditions, yet have similar 3D struc... read more 
Computer Vision and Pattern Recognition cs.LG

Glance-or-Gaze: Incentivizing LMMs to Adaptively Focus Search via Reinforcement Learning

arXiv Jan 20, 2026
Large Multimodal Models (LMMs) have achieved remarkable success in visual understanding, yet they struggle with knowledge-intensive queries involving long-tail entities or evolving information due to static parametric knowledge. Recent search-augment... read more 
Computer Vision and Pattern Recognition cs.AI

VTONGuard: Automatic Detection and Authentication of AI-Generated Virtual Try-On Content

arXiv Jan 20, 2026
With the rapid advancement of generative AI, virtual try-on (VTON) systems are becoming increasingly common in e-commerce and digital entertainment. However, the growing realism of AI-generated try-on content raises pressing concerns about authentici... read more 
Computer Vision and Pattern Recognition

DExTeR: Weakly Semi-Supervised Object Detection with Class and Instance Experts for Medical Imaging

arXiv Jan 20, 2026
Detecting anatomical landmarks in medical imaging is essential for diagnosis and intervention guidance. However, object detection models rely on costly bounding box annotations, limiting scalability. Weakly Semi-Supervised Object Detection (WSSOD) wi... read more 
Computer Vision and Pattern Recognition

Harmonizing the Deep: A Unified Information Pipeline for Robust Marine Biodiversity Assessment Across Heterogeneous Domains

arXiv Jan 20, 2026
Marine biodiversity monitoring requires scalability and reliability across complex underwater environments to support conservation and invasive-species management. Yet existing detection solutions often exhibit a pronounced deployment gap, with perfo... read more 
Computer Vision and Pattern Recognition cs.LG

Component systems: do null models explain everything?

arXiv Jan 20, 2026
Component systems - ensembles of realizations built from a shared repertoire of modular parts - are ubiquitous in biological, ecological, technological, and socio-cultural domains. From genomes to texts, cities, and software, these systems exhibit st... read more 
Statistical Mechanics q-bio.OT

Equivariant Learning for Unsupervised Image Dehazing

arXiv Jan 20, 2026
Image Dehazing (ID) aims to produce a clear image from an observation contaminated by haze. Current ID methods typically rely on carefully crafted priors or extensive haze-free ground truth, both of which are expensive or impractical to acquire, part... read more 
Computer Vision and Pattern Recognition eess.IV

SHARE: A Fully Unsupervised Framework for Single Hyperspectral Image Restoration

arXiv Jan 20, 2026
Hyperspectral image (HSI) restoration is a fundamental challenge in computational imaging and computer vision. It involves ill-posed inverse problems, such as inpainting and super-resolution. Although deep learning methods have transformed the field ... read more 
Image and Video Processing cs.CV

Likelihood-Separable Diffusion Inference for Multi-Image MRI Super-Resolution

arXiv Jan 20, 2026
Diffusion models are the current state-of-the-art for solving inverse problems in imaging. Their impressive generative capability allows them to approximate sampling from a prior distribution, which alongside a known likelihood function permits poste... read more 
Computer Vision and Pattern Recognition

Generalizing Abstention for Noise-Robust Learning in Medical Image Segmentation

arXiv Jan 20, 2026
Label noise is a critical problem in medical image segmentation, often arising from the inherent difficulty of manual annotation. Models trained on noisy data are prone to overfitting, which degrades their generalization performance. While a number o... read more 
Computer Vision and Pattern Recognition cs.AI
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