Ensemble of fine-tuned machine learning models for hysterectomy prediction in pregnant women using magnetic resonance images [0.03%]
使用磁共振图像对孕妇进行子宫切除术预测的微调机器学习模型集成
Vishnu Vardhan Reddy Kanamata Reddy,Michael Villordon,Quyen N Do et al.
Vishnu Vardhan Reddy Kanamata Reddy et al.
Purpose: Identifying pregnant patients at high risk of hysterectomy before giving birth informs clinical management and improves outcomes. We aim to develop machine learning models to predict hysterectomy in pregnant wome...
Using a fully automated, quantitative fissure integrity score extracted from chest CT scans of emphysema patients to predict endobronchial valve response [0.03%]
利用来自肺气肿患者的胸部CT扫描的全自动化定量裂隙完整性评分来预测支气管内瓣膜反应
Dallas K Tada,Grace H Kim,Jonathan G Goldin et al.
Dallas K Tada et al.
Purpose: We aim to develop and validate a prediction model using a previously developed fully automated quantitative fissure integrity score (FIS) extracted from pre-treatment CT images to identify suitable candidates for...
HID-CON: weakly supervised intrahepatic cholangiocarcinoma subtype classification of whole slide images using contrastive hidden class detection [0.03%]
对比隐藏类检测在弱监督下的整个幻灯片图像中的肝内胆管癌亚型分类（HID-CON）
Jing Wei Tan,Kyoungbun Lee,Won-Ki Jeong
Jing Wei Tan
Purpose: Biliary tract cancer, also known as intrahepatic cholangiocarcinoma (IHCC), is a rare disease that shows no clear symptoms during its early stage, but its prognosis depends highly on the cancer subtype. Hence, an...
Impact of menopause and age on breast density and background parenchymal enhancement in dynamic contrast-enhanced magnetic resonance imaging [0.03%]
更年期和年龄对动态对比增强磁共振成像中乳腺密度和背景实质强化的影响
Grey Kuling,Jennifer D Brooks,Belinda Curpen et al.
Grey Kuling et al.
Purpose: Breast density (BD) and background parenchymal enhancement (BPE) are important imaging biomarkers for breast cancer (BC) risk. We aim to evaluate longitudinal changes in quantitative BD and BPE in high-risk women...
Distributed and networked analysis of volumetric image data for remote collaboration of microscopy image analysis [0.03%]
体积图像数据的分布式和网络化分析以实现显微镜图像分析的远程协作
Alain Chen,Shuo Han,Soonam Lee et al.
Alain Chen et al.
Purpose: The advancement of high-content optical microscopy has enabled the acquisition of very large three-dimensional (3D) image datasets. The analysis of these image volumes requires more computational resources than a...
Wennan Zhao,Trevor Kuhlengel,Qi Chang et al.
Wennan Zhao et al.
Purpose: Lung cancer remains the leading cause of cancer death. This has brought about a critical need for managing peripheral regions of interest (ROIs) in the lungs, be it for cancer diagnosis, staging, or treatment. Th...
Accurate volume image reconstruction for digital breast tomosynthesis with directional-gradient and pixel sparsity regularization [0.03%]
具有方向梯度和像素稀疏正则化的数字乳腺断层合成的精确体积图像重建方法
Emil Y Sidky,Xiangyi Wu,Xiaoyu Duan et al.
Emil Y Sidky et al.
Purpose: We aim to develop accurate volumetric quantitative imaging of iodinated contrast agent (ICA) in contrast-enhanced digital breast tomosynthesis (DBT). ...
SAM-MedUS: a foundational model for universal ultrasound image segmentation [0.03%]
SAM-MedUS：一种用于通用超声图像分割的基础模型
Feng Tian,Jintao Zhai,Jinru Gong et al.
Feng Tian et al.
Purpose: Segmentation of ultrasound images for medical diagnosis, monitoring, and research is crucial, and although existing methods perform well, they are limited by specific organs, tumors, and image devices. Applicatio...
Identifying texture features from structural magnetic resonance imaging scans associated with Tourette's syndrome using machine learning [0.03%]
使用机器学习从结构磁共振成像扫描中识别与妥瑞氏症相关的纹理特征
Murilo Costa de Barros,Kauê Tartarotti Nepomuceno Duarte,Chia-Jui Hsu et al.
Murilo Costa de Barros et al.
Purpose: Tourette syndrome (TS) is a neurodevelopmental disorder characterized by neurophysiological and neuroanatomical changes, primarily affecting individuals aged 2 to 18. Involuntary motor and vocal tics are common f...
OPHash: learning of organ and pathology context-sensitive hashing for medical image retrieval [0.03%]
OPHash：学习组织和疾病敏感的哈希方法用于医学图像检索
Asim Manna,Rakshith Sathish,Ramanathan Sethuraman et al.
Asim Manna et al.
Purpose: Retrieving images of organs and their associated pathologies is essential for evidence-based clinical diagnosis. Deep neural hashing (DNH) has demonstrated the ability to retrieve images fast on large datasets. C...