Artificial Intelligence Medical Compendium

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

Showing 39,371 to 39,380 of 223,737 articles

Knot-10:A Tightness-Stratified Benchmark for Real-World Knot Classification with Topological Difficulty Analysis

arXiv Mar 24, 2026
Physical knot classification is a fine-grained visual classification (FGVC) scenario in which appearance cues are deliberately suppressed: different classes share the same rope material, color, and background, and class identity resides primarily in ... read more 
Computer Vision and Pattern Recognition

Mamba-driven MRI-to-CT Synthesis for MRI-only Radiotherapy Planning

arXiv Mar 24, 2026
Radiotherapy workflows for oncological patients increasingly rely on multi-modal medical imaging, commonly involving both Magnetic Resonance Imaging (MRI) and Computed Tomography (CT). MRI-only treatment planning has emerged as an attractive alternat... read more 
Computer Vision and Pattern Recognition

Curriculum-Driven 3D CT Report Generation via Language-Free Visual Grafting and Zone-Constrained Compression

arXiv Mar 24, 2026
Automated radiology report generation from 3D computed tomography (CT) volumes is challenging due to extreme sequence lengths, severe class imbalance, and the tendency of large language models (LLMs) to ignore visual tokens in favor of linguistic pri... read more 
Computer Vision and Pattern Recognition cs.AI

ARGENT: Adaptive Hierarchical Image-Text Representations

arXiv Mar 24, 2026
Large-scale Vision-Language Models (VLMs) such as CLIP learn powerful semantic representations but operate in Euclidean space, which fails to capture the inherent hierarchical structure of visual and linguistic concepts. Hyperbolic geometry, with its... read more 
Computer Vision and Pattern Recognition cs.LG

Pose-Free Omnidirectional Gaussian Splatting for 360-Degree Videos with Consistent Depth Priors

arXiv Mar 24, 2026
Omnidirectional 3D Gaussian Splatting with panoramas is a key technique for 3D scene representation, and existing methods typically rely on slow SfM to provide camera poses and sparse points priors. In this work, we propose a pose-free omnidirectiona... read more 
Computer Vision and Pattern Recognition

ViBe: Ultra-High-Resolution Video Synthesis Born from Pure Images

arXiv Mar 24, 2026
Transformer-based video diffusion models rely on 3D attention over spatial and temporal tokens, which incurs quadratic time and memory complexity and makes end-to-end training for ultra-high-resolution videos prohibitively expensive. To overcome this... read more 
Computer Vision and Pattern Recognition

Strain-Parameterized Coupled Dynamics and Dual-Camera Visual Servoing for Aerial Continuum Manipulators

arXiv Mar 24, 2026
Tendon-driven aerial continuum manipulators (TD-ACMs) combine the maneuverability of uncrewed aerial vehicles (UAVs) with the compliance of lightweight continuum robots (CRs). Existing coupled dynamic modeling approaches for TD-ACMs incur high comput... read more 
Robotics cs.CV

An Explainable AI-Driven Framework for Automated Brain Tumor Segmentation Using an Attention-Enhanced U-Net

arXiv Mar 24, 2026
Computer-aided segmentation of brain tumors from MRI data is of crucial significance to clinical decision-making in diagnosis, treatment planning, and follow-up disease monitoring. Gliomas, owing to their high malignancy and heterogeneity, represent ... read more 
Computer Vision and Pattern Recognition

Central Dogma Transformer III: Interpretable AI Across DNA, RNA, and Protein

arXiv Mar 24, 2026
Biological AI models increasingly predict complex cellular responses, yet their learned representations remain disconnected from the molecular processes they aim to capture. We present CDT-III, which extends mechanism-oriented AI across the full cent... read more 
Machine Learning q-bio.GN

Harnessing Lightweight Transformer with Contextual Synergic Enhancement for Efficient 3D Medical Image Segmentation

arXiv Mar 24, 2026
Transformers have shown remarkable performance in 3D medical image segmentation, but their high computational requirements and need for large amounts of labeled data limit their applicability. To address these challenges, we consider two crucial aspe... read more 
Computer Vision and Pattern Recognition eess.IV
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