Canaries in the Coal Mine: What the APDR Survey Reveals About Academic Radiology's Challenges and Opportunities [0.03%]
矿井中的金丝雀：APDR调查揭示的学术放射学面临的挑战和机遇
Justin G Peacock
Justin G Peacock
A Cascaded Segmentation-Classification Deep Learning Framework for Preoperative Prediction of Occult Peritoneal Metastasis and Early Recurrence in Advanced Gastric Cancer [0.03%]
术前预测晚期胃癌隐匿性腹膜转移和早期复发的级联分割-分类深度学习框架
Tianxiu Zou,Peng Chen,Ting Wang et al.
Tianxiu Zou et al.
Purpose: To develop a cascaded deep learning (DL) framework integrating tumor segmentation with metastatic risk stratification for preoperative prediction of occult peritoneal metastasis (OPM) in advanced gastric cancer (...
Early Diastolic Dysfunction Detection in Hypertension: CMR-Derived Left Atrial Strain [0.03%]
基于心脏磁共振的左心房应变在高血压早期舒张功能障碍检测中的价值
Weiwei Liao,Bin Fang,Yuan Kang et al.
Weiwei Liao et al.
Rationale and objectives: This study aimed to investigate the role of cardiac magnetic resonance (CMR)-derived left atrial (LA) strain parameters in evaluating early cardiac dysfunction in hypertensive patients and to ass...
Deep Learning Based Multiomics Model for Risk Stratification of Postoperative Distant Metastasis in Colorectal Cancer [0.03%]
基于深度学习的多组学模型在结直肠癌术后远处转移风险分层中的应用研究
Xiuzhen Yao,Xiaoyu Han,Danjiang Huang et al.
Xiuzhen Yao et al.
Rationale and objectives: To develop deep learning-based multiomics models for predicting postoperative distant metastasis (DM) and evaluating survival prognosis in colorectal cancer (CRC) patients. ...
Automated Kidney Tumor Segmentation in CT Images Using Deep Learning: A Multi-Stage Approach [0.03%]
基于深度学习的CT图像肾脏肿瘤分割：一种多阶段方法
Hung-Cheng Kan,Geng-Ming Fan,Ming-Hao Wei et al.
Hung-Cheng Kan et al.
Rationale and objectives: Computed tomography (CT) remains the primary modality for assessing renal tumors; however, tumor identification and segmentation rely heavily on manual interpretation by clinicians, which is time...
Voxel-level Radiomics and Deep Learning Based on MRI for Predicting Microsatellite Instability in Endometrial Carcinoma: A Two-center Study [0.03%]
基于MRI的体素级别影像组学和深度学习预测子宫内膜癌微卫星不稳定性：一项两中心研究
Chen-Hong Tian,Peng Sun,Ke-Yuan Xiao et al.
Chen-Hong Tian et al.
Rationale and objectives: To develop and validate a non-invasive deep learning model that integrates voxel-level radiomics with multi-sequence MRI to predict microsatellite instability (MSI) status in patients with endome...
Providing Radiology Services at Another Institution: Cultural and Contractual Issues [0.03%]
在另一机构提供放射服务：文化与合同问题
Jeffrey W Dunkle,Kevin L Smith,Richard B Gunderman
Jeffrey W Dunkle
Saumya S Gurbani,Ichiro Ikuta,Mina S Makary et al.
Saumya S Gurbani et al.
Medical imaging plays an increasingly central role in the diagnostic workup and management of patients. As imaging technologies evolve, the radiology community faces the challenge of balancing the diagnostic benefits of medical imaging with...
Comparative Analysis of MRI Features and Overall Survival: IDH-Wildtype Diffuse Lower-grade Glioma and Glioblastoma in Adults [0.03%]
IDH野生型低级别和高级别胶质瘤的MRI表现及生存分析
Xiaojun Yu,Xiaoxiao Ma,Junfeng Zhang et al.
Xiaojun Yu et al.
Rationale and objectives: In depth comparison of imaging features and overall survival (OS) between IDH wild-type diffuse lower-grade glioma and glioblastoma (GB), providing precise guidance for early risk stratification ...
A Preliminary Study on an Intelligent Segmentation and Classification Model for Amygdala-Hippocampus MRI Images in Alzheimer's Disease [0.03%]
阿尔茨海默病磁共振弥散加权成像的智能图像分割及分类模型初步研究
Siyu Liu,Kun Zhou,Daoying Geng
Siyu Liu
Background: This study developed a deep learning model for segmenting and classifying the amygdala-hippocampus in Alzheimer's disease (AD), using a large-scale neuroimaging dataset to improve early AD detection and interv...