Machine learning evaluation of pneumonia severity: subgroup performance in the Medical Imaging and Data Resource Center modified radiographic assessment of lung edema mastermind challenge [0.03%]
机器学习评估肺炎严重程度：Medical Imaging and Data Resource Center修改的放射性肺水肿评估大师赛中各子群体的表现
Karen Drukker,Samuel G Armato rd,Lubomir Hadjiiski et al.
Karen Drukker et al.
Purpose: The Medical Imaging and Data Resource Center Mastermind Grand Challenge of modified radiographic assessment of lung edema (mRALE) tasked participants with developing machine learning techniques for automated COVI...
BigReg: an efficient registration pipeline for high-resolution X-ray and light-sheet fluorescence microscopy [0.03%]
高效的大规模X射线和薄片荧光显微镜图像配准方法 BigReg
Siyuan Mei,Fuxin Fan,Mareike Thies et al.
Siyuan Mei et al.
Purpose: We aim to propose a reliable registration pipeline tailored for multimodal mouse bone imaging using X-ray microscopy (XRM) and light-sheet fluorescence microscopy (LSFM). These imaging modalities have emerged as ...
Bowen Xiang,Jon S Heiselman,Michael I Miga
Bowen Xiang
Purpose: Intraoperative liver deformation and the need to glance repeatedly between the operative field and a remote monitor undermine the precision and workflow of image-guided liver surgery. Existing mixed reality (MR) ...
DMM-UNet: dual-path multi-scale Mamba UNet for medical image segmentation [0.03%]
双路径多尺度Mamba U网在医学图像分割中的应用
Liquan Zhao,Mingxia Cao,Yanfei Jia
Liquan Zhao
Purpose: State space models have shown promise in medical image segmentation by modeling long-range dependencies with linear complexity. However, they are limited in their ability to capture local features, which hinders ...
Deep-learning-based estimation of left ventricle myocardial strain from echocardiograms with occlusion artifacts [0.03%]
基于深度学习的带遮挡标记的超声心动图左心室心肌应变估计方法研究
Alan Romero-Pacheco,Nidiyare Hevia-Montiel,Blanca Vazquez et al.
Alan Romero-Pacheco et al.
Purpose: We present a deep-learning-based methodology for estimating deformation in 2D echocardiograms. The goal is to automatically estimate the longitudinal strain of the left ventricle (LV) walls in images affected by ...
Gamification for emergency radiology education and image perception: stab the diagnosis [0.03%]
急症放射学教育和影像判读能力的激励方法：“诊断刺刺乐”游戏教学法
William F Auffermann,Nathan Barber,Ryan Stockard et al.
William F Auffermann et al.
Purpose: Gamification can be a helpful adjunct to education and is increasingly used in radiology. We aim to determine if using a gamified framework to teach medical trainees about emergency radiology can improve perceptu...
Full-head segmentation of MRI with abnormal brain anatomy: model and data release [0.03%]
异常大脑解剖的MRI全脑分割：模型和数据发布
Andrew M Birnbaum,Adam Buchwald,Peter Turkeltaub et al.
Andrew M Birnbaum et al.
Purpose: Our goal was to develop a deep network for whole-head segmentation, including clinical magnetic resonance imaging (MRI) with abnormal anatomy, and compile the first public benchmark dataset for this purpose. We c...
Segmentation variability and radiomics stability for predicting triple-negative breast cancer subtype using magnetic resonance imaging [0.03%]
基于磁共振成像的影像组学预测三阴性乳腺癌分子亚型的可变性和稳定性研究
Isabella Cama,Alejandro Guzmán,Cristina Campi et al.
Isabella Cama et al.
Purpose: Many studies caution against using radiomic features that are sensitive to contouring variability in predictive models for disease stratification. Consequently, metrics such as the intraclass correlation coeffici...
Maryellen L Giger,Susan Astley Theodossiadis,Karen Drukker et al.
Maryellen L Giger et al.
The editorial introduces the JMI Special Issue on Advances in Breast Imaging, reflecting on the current forefront of breast imaging research. © 2025 Soc...
Fine-grained multiclass nuclei segmentation with molecular empowered all-in-SAM model [0.03%]
一种基于分子信息增强的全样本模型的细粒度多类别细胞核分割方法
Xueyuan Li,Can Cui,Ruining Deng et al.
Xueyuan Li et al.
Purpose: Recent developments in computational pathology have been driven by advances in vision foundation models (VFMs), particularly the Segment Anything Model (SAM). This model facilitates nuclei segmentation through tw...