CLEAR-AI: confounder-aware learning for equitable and accurate reasoning in AI for diagnosis [0.03%]
CLEAR-AI：用于诊断的AI中公平而准确推理的混杂因素感知学习
Vedant Joshi,Ramon Correa,Avisha Das et al.
Vedant Joshi et al.
Purpose: A critical challenge impeding the deployment of artificial intelligence (AI) models in healthcare lies in implicit bias against multiple correlated sensitive attributes. ...
Synthesizing vocal tract magnetic resonance imaging sequences with phoneme-aware diffusion models [0.03%]
基于音素感知的扩散模型合成声学通道磁共振影像序列
Paula Andrea Perez-Toro,Tomas Arias-Vergara,Lukas Buess et al.
Paula Andrea Perez-Toro et al.
Purpose: Real-time speech MRI offers critical insights into articulatory dynamics for diagnostics, therapy, and speech science, but direct speech-to-MRI mapping remains highly challenging. We present a diffusion-based fra...
Multi-institutional classification of fibroglandular tissue and background parenchymal enhancement in breast MRI using deep learning [0.03%]
基于深度学习的乳腺MRI中纤维腺体组织与背景间质增强的多中心分类研究
Kai Geissler,Hans Meine,Hendrik Laue et al.
Kai Geissler et al.
Purpose: The amount of fibroglandular tissue (FGT) and background parenchymal enhancement (BPE) are evaluated as part of the BI-RADS reporting standard for the diagnosis of breast cancer in magnetic resonance imaging (MRI...
Pediatric-specific computer-aided detection of lung nodules in computed tomography scans [0.03%]
针对儿科CT扫描肺结节的计算机辅助检测技术
Russell C Hardie,Dylan Flaute,Barath N Narayanan et al.
Russell C Hardie et al.
Purpose: In pediatric patients with cancer, the presence of small lung nodules and micronodules on computed tomography (CT) scans can be clinically significant and indicative of metastatic cancer. Lung nodule computer-aid...
Author-Centric AI Pre-Review: Interpreting Science Before It Is Judged [0.03%]
以作者为中心的AI预审：在科学被评判之前进行解读
Bennett A Landman
Bennett A Landman
The editorial explores an author-centric approach to AI in scientific publishing, arguing for the use of AI as a pre-submission self-review tool to help authors anticipate interpretation, clarify arguments, and strengthen rigor, while prese...
Golriz Hosseinimanesh,Farida Cheriet,Ammar Alsheghri et al.
Golriz Hosseinimanesh et al.
Purpose: Deep learning algorithms offer the potential to automate dental crown generation, reducing time-intensive manual design in dental laboratories. However, achieving crowns suitable for direct clinical use requires ...
Head-to-head comparisons of breast density assessment models using deep learning on digital and synthetic mammograms [0.03%]
基于数字和合成乳腺X线影像的深度学习乳腺密度评估模型的对比研究
Krisha Anant,Juanita Hernández López,Junjie Cui et al.
Krisha Anant et al.
Purpose: We aim to evaluate the performance of different deep learning (DL) architectures in breast density classification using digital mammograms (DMs) and synthetic mammograms (SMs) from digital breast tomosynthesis (D...
MILU: a consensus ensemble benchmark for multimodal medical imaging lecture understanding [0.03%]
MILU：多模态医学影像讲座理解的共识集合基准
Md Motaleb Hossen Manik,Md Zabirul Islam,Ge Wang
Md Motaleb Hossen Manik
Purpose: Vision-language models (VLMs) are increasingly used to interpret multimodal educational materials, yet their reliability on diagram-, equation-, and text-dense scientific lecture slides remains poorly understood....
Filter2Noise: a framework for interpretable and zero-shot low-dose CT image denoising [0.03%]
基于解释性和零样本特性的低剂量CT图像降噪框架
Yipeng Sun,Linda-Sophie Schneider,Siyuan Mei et al.
Yipeng Sun et al.
Purpose: Deep learning has achieved remarkable progress in low-dose computed tomography (LDCT) denoising; however, radiologists struggle to trust black-box models they cannot verify or control. Zero-shot methods eliminate...
Parameter-efficient deep-learning-based model for segmentation with radiomic feature extraction [0.03%]
基于参数高效微调的端到端分割与影像组学模型
Daniel Sleiman,Navchetan Awasthi
Daniel Sleiman
Purpose: Magnetic resonance imaging (MRI), particularly dynamic contrast-enhanced MRI (DCE-MRI), plays a vital role in breast cancer assessment by highlighting tumor regions. Accurate 3D segmentation of tumors can signifi...