Radiomics and AI in Medical Imaging

• 2770 · PDF astril：面向放射影像库的自动化分割工具包 astril : Automated segmentation toolkit for radiology image libraries Alexander L. Ling, C. Zoe Linke, Christopher M. Jannotta, Data Science Teamlab, E. Antonio Chiocca
• 2771 · PDF 整合基于图像和文本的AI改进从全切片病理图像中识别转移部位 Integrating image and text-based AI improves identification of metastatic sites from whole-slide pathology images Yixin Chen, Ziyu Su, Muhammad Khalid Niazi, Anil Vasdev Parwani, Elshad Hasanov
• 2772 · PDF 用于预测不可切除肝细胞癌中基于lenvatinib的治疗方案应答和结局的无创人工智能系统 Noninvasive artificial intelligence system for prediction of lenvatinib based therapeutic regimens response and outcome in unresectable hepatocellular carcinoma Bo Chen, Yuqian Gan, Enguang Zou, Yi Wang, Gang Chen
• 2773 · PDF 基于多区域CT的影像组学融合预测与肺腺癌相关的病理污染物指数 Multi-regional CT-based radiomics fusion predicts pathological pollutant index associated with lung adenocarcinoma Yutong Li, Xiaoxi Pan, Abishek Balachandra, Chingyi Young, Maria Esther Salvatierra, Carmen Behrens, Luisa Maren Solis Soto, Yinyin Yuan, Chengyue Wu
• 2774 · PDF 转移性尤因肉瘤中的肺结节追踪实现个体化预测模型 Pulmonary nodule tracking in metastatic Ewing sarcoma enables personalized predictive models Kevin A. Murgas, Shambhavi Kurup, Maureiq Ojwang, Rene Malazarte, Danh D. Truong, Heiko Enderling, Joseph A. Ludwig
• 2775 · PDF 深度学习CT生物标志物在模拟随机II期NSCLC试验中改善早期疗效检测 Deep-learning CT biomarker improves early efficacy detection in simulated randomized phase II NSCLC trials Chiharu Sako, Brenda F. Kurland, Taly G. Schmidt, Dwight H. Owen, Arpan A. Patel, Nicholas C. Love, Olivier Gevaert, George R. Simon, Ravi B. Parikh, Petr Jordan
• 2776 · PDF CT影像组学在gBRCA1/2和PALB2突变的晚期胰腺癌患者中的预后价值 Prognostic value of CT radiomics in patients with gBRCA1/2 and PALB2 and advanced pancreas cancer Sonal Gandhi, Jayasree Chakraborty, Hadi Ghahremannezhad, Richard Do, Natally Horvat, Kenneth H. Yu, Wungki Park, Eileen M. O'Reilly
• 2777 · PDF 多期相CT扫描的自动对比期相分类 Automatic contrast phase classification of polyphasic CT scans Georgia Hughes, Mayank Patwari, Yi Wei, Michael Parker, James Parkin, Zhenning Zhang, Aleksandr Filippov
• 2778 · PDF 利用癌症规模基础模型从全切片图像中学习空间转录组模式 Learning spatial transcriptomic patterns from whole-slide images with a cancer-scale foundation model Minsoo Lee, Soonyoung Lee, Tae Hyun Hwang, Jongseong Jang
• 2779 · PDF 结合乳腺癌多基因风险评分的MIRAI 5年风险模型的开发与评估 Development and evaluation of a MIRAI 5-year risk model with a breast cancer polygenic risk score Christopher G. Scott, Peter Kraft, Imon Banerjee, Ramon Correa Medero, Aaron D. Norman, Fergus J. Couch, Karla Kerlikowske, Stacey J. Winham, Celine M. Vachon
• 2782 · PDF 使用AI模型对肝硬化患者对比增强MRI上的肝细胞癌病灶进行自动分割 Automated segmentation of hepatocellular carcinoma lesions on contrast-enhanced MRI using an AI model in patients with cirrhosis Emma J. Stevenson, Nathan Lay, Stephanie A. Harmon, Haoyue Zhang, Fahmida Haque, Peter Choyke, Theo Heller, Ross Filice, Baris Turkbey, Christine Hsu
• 2783 · PDF 使用普遍可及、跨平台、AI驱动的应用程序进行肺癌智能检测（LUCID） Lung cancer intelligent detection (LUCID) using a universally accessible, cross-platform, AI-powered application Gowrishankar Palaniswamy, Elangovan Krishnan, Jansi R. Sethuraj, Muhammad Waqas Khan, Aravind Raghavan
• 2784 · PDF 整合空间转录组学与MRI揭示与前列腺癌克隆异质性一致的独特放射-空间基因组图谱 Integrating spatial transcriptomics with MRI reveals distinct radio-spatial genomic profile concordant with prostate cancer clonal heterogeneity Thineskrishna Anbarasan, Sandy Figiel, Max Beesley, Wencheng Yin, Ruth McPherson, Richard Colling, Freddie Hamdy, Richard J. Bryant, Bartlomiej Papiez, Alastair D. Lamb, Ian Mills
• 2785 · PDF 利用治疗前MRI评估乳腺癌复发风险：一项基于多中心数据的迁移学习研究 Assessing the risk of breast cancer recurrence with pre-treatment MRI: A transfer learning study on multicenter data Kanika Bhalla, Adrian Sanchez, José Marcio Luna, Tabassum Ahmad, Debbie L. Bennett, Andrew A. Davis, Aimilia Gastounioti
• 2786 · PDF CorrectionNet：一种用于改进医学图像分割的轻量级残差精修框架 CorrectionNet: A lightweight residual refinement framework for improving medical image segmentation Antoine Azar, Cally Lin, Naryeong Kim
• 2787 · PDF 利用人工智能（AI）对接受一线（1L）系统治疗的IV期结直肠癌（CRC）患者进行基于影像的预后评估（IPRO） Evaluation of imaging-based prognostication (IPRO) using artificial intelligence (AI) in stage IV colorectal cancer (CRC) patients treated with first-line (1L) systemic therapy Mohammed A. Alvi, Ronald Bridges, Marina Salluzzi, Felipe Soares Torres, Kartik Jhaveri, Natasha B. Leighl, John Riskas, Shahid Haider, Vignesh Sivan, Oleksandra Samodorova, Jay Hennesy, Duoaud Shah, FELIX BALDAUF-LENSCHEN, Omar F. Khan
• 2788 2788 用于全面肿瘤负荷评估的自动病灶分类的多中心开发：解决RECIST在试验与实践之间的脱节 Multi-site development of automated lesion classification for comprehensive tumor burden assessment: Addressing the RECIST trial-practice disconnect Ella Pavlechko, Xi Jiang, Ravikumar Komandur Elayavilli, Eleanor McCabe, Jon McDunn, Sean Khozin
• 2789 · PDF 利用基础模型从内镜图像预测浅表性食管癌的浸润深度 Depth prediction in superficial esophageal cancer using a foundation model from endoscopic images Sehun Kim, Sohyung Kim, Hyosoon Yoo, Hyuk Lee, Yang Won Min
• 2790 · PDF 基于基础模型、利用完整未经筛选的EGD图像序列进行胃癌分期 Foundation model-based gastric cancer staging from complete, uncurated EGD image sequences Sehun Kim, Hyosoon Yoo, Yang Won Min, Hyuk Lee
• 2791 · PDF 通过在潜在空间中由Kaniadakis向量嵌入提取的多模态放射组学表型，对术后GBM患者进行基于深度学习的生存预测 Deep learning-based survival prediction of post-operative GBM patients via multimodal radiomic phenotypes drawn from Kaniadakis vector embedding in latent space Roy Nasr, Bardia Rodd
• 2792 · PDF 利用PR-等距引导的深度学习解码基于CT的肿瘤异质性并改善NSCLC预后评估 Leveraging PR-isometric guided deep learning to decode CT-based tumor heterogeneity and enhanced NSCLC prognosis Joel Thomas, Blake Gilbert, Harmen Siezen, Lan Ma, Jimmy J Azarnoosh, Bardia Rodd

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