Artificial Intelligence Medical Compendium

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

Showing 20,751 to 20,760 of 216,088 articles

Set-Based Groupwise Registration for Variable-Length, Variable-Contrast Cardiac MRI

arXiv May 11, 2026
Quantitative cardiac magnetic resonance imaging (MRI) enables non-invasive myocardial tissue characterization but relies on robust motion correction within these variable-length, variable-contrast image sequences. Groupwise registration, which simult... read more 
Image and Video Processing cs.CV

SenseBench: A Benchmark for Remote Sensing Low-Level Visual Perception and Description in Large Vision-Language Models

arXiv May 11, 2026
Low-level visual perception underpins reliable remote sensing (RS) image analysis, yet current image quality assessment (IQA) methods output uninterpretable scalar scores rather than characterizing physics-driven RS degradations, deviating markedly f... read more 
Computer Vision and Pattern Recognition cs.AI

Polygon-mamba: Retinal vessel segmentation using polygon scanning mamba and space-frequency collaborative attention

arXiv May 11, 2026
Retinal vessel segmentation is crucial for diagnosis and assessment of ocular diseases. Notably, segmentation of small retinal vessels has been consistently recognized as a challenging and complex task. To tackle this challenge, we design a hybrid CN... read more 
Computer Vision and Pattern Recognition

FrequencyCT: Frequency domain pseudo-label generation for self-supervised low-dose CT denoising

arXiv May 11, 2026
Despite extensive research on computed tomography (CT) denoising, few studies exploit projection-domain data characteristics to mitigate noise correlation. To address this, this work proposes FrequencyCT, the first zero-shot self-supervised method fo... read more 
Computer Vision and Pattern Recognition

MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image

arXiv May 11, 2026
Tabular Foundation Models have recently established the state of the art in supervised tabular learning, by leveraging pretraining to learn generalizable representations of numerical and categorical structured data. However, they lack native support ... read more 
Machine Learning cs.CL cs.CV

Hypergraph-Enhanced Training-Free and Language-Free Few-Shot Anomaly Detection

arXiv May 11, 2026
Few-shot anomaly detection (FSAD) has made significant strides, yet existing methods still face critical challenges: (i) dependence on task- or dataset-specific training/fine-tuning, (ii) reliance on language supervision or carefully hand-crafted pro... read more 
Computer Vision and Pattern Recognition

Product-of-Gaussian-Mixture Diffusion Models for Joint Nonlinear MRI Reconstruction

arXiv May 11, 2026
Recently, diffusion models have attracted considerable attention for magnetic resonance image reconstruction due to their high sample quality. However, most existing methods rely on large networks with opaque time-conditioning mechanisms, and require... read more 
Computer Vision and Pattern Recognition

GenMed: A Pairwise Generative Reformulation of Medical Diagnostic Tasks

arXiv May 11, 2026
Data-driven medical AI is traditionally formulated as a discriminative mapping from input $X$ to output $Y$ via a learned function $f$, which does not generalize well across heterogeneous data and modalities encountered in real-world clinical setting... read more 
Computer Vision and Pattern Recognition

bViT: Investigating Single-Block Recurrence in Vision Transformers for Image Recognition

arXiv May 11, 2026
Vision Transformers (ViTs) are built by stacking independently parameterized blocks, but it remains unclear how much of this depth requires layer specific transformations and how much can be realized through recurrent computation. We study this quest... read more 
Computer Vision and Pattern Recognition cs.AI

Not Blind but Silenced: Rebalancing Vision and Language via Adversarial Counter-Commonsense Equilibrium

arXiv May 11, 2026
During MLLM decoding, attention often abnormally concentrates on irrelevant image tokens. While existing research dismisses this as invalid noise and forcibly redirects attention to compel focusing on key image information, we argue these tokens are ... read more 
Computer Vision and Pattern Recognition cs.LG
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