imaging

“EfficientNet-B0 outperformed DenseNet121, achieving an accuracy of 84.6%, F1-score of 0.8899, and MCC of 0.6849.”

“These findings strongly support a human-in-the-loop (HITL) workflow in which the on-premise LLM serves as a collaborative tool, not a full replacement.”

“AI misses nearly one-third of breast cancers, study finds”

“A tool for spotting pancreatic cancer in routine CT scans has had promising results, one example of how China is racing to apply A.I. to medicine's tough problems.”

“将技术的复杂性留给自己，将创作的纯粹性还给用户。”

“The article's context, from ArXiv, suggests it's a research paper.”

“FETAL-GAUGE is a benchmark for assessing vision-language models in Fetal Ultrasound.”

“The research focuses on a 'Tool Bottleneck Framework' for medical image understanding.”

“The paper uses a Latent Diffusion Model for thermal face image translation.”

“The article's context highlights the use of AI to address the specifics of multi-label long-tail data within an X-ray analysis context.”

“The research focuses on segmentation of breast ultrasound images using a novel multimodal approach.”

“ASCHOPLEX encounters Dafne: a federated continuous learning project for the generalizability of the Choroid Plexus automatic segmentation”

“The article presents a DeepSeek-powered AI system.”

“The context provides minimal information beyond the title and source, focusing on a technical aspect of neuroimaging research.”

“The research focuses on the combinatorial explosion problem in deformable medical image registration.”

“The research focuses on 3D cardiac shape reconstruction.”

“InvCoSS utilizes inversion-driven continual self-supervised learning.”

“Automatic Neuronal Activity Segmentation in Fast Four Dimensional Spatio-Temporal Fluorescence Imaging using Bayesian Approach”

“brat is a method for Brain MRI analysis.”

“The article's core focus is accelerating SMWI reconstruction.”

“The article focuses on imaging the LkCa 15 system in polarimetry and total intensity without self-subtraction artefacts.”

“The article's focus is on using a two-stream network with global-local feature fusion.”

“SAMM2D is a Scale-Aware Multi-Modal 2D Dual-Encoder.”

“The research focuses on the application of 3D diffusion models for CT reconstruction.”

“The research focuses on temporally consistent monocular depth estimation.”

“MedNeXt-v2 focuses on scaling 3D ConvNets for large-scale supervised representation learning in medical image segmentation.”

“The study uses neural networks to estimate spatially resolved radiation fields.”

“The study focuses on self-supervised learning for improving MRI resolution.”

“The research focuses on a unified FLAIR hyperintensity segmentation model.”

“Guided progressive reconstructive imaging: a new quantization-based framework for low-dose, high-throughput and real-time analytical ptychography”