Contrast-Enhanced Mammography-Based Radiomics for Predicting Ductal Carcinoma In Situ in Breast Cancer [0.03%]
基于乳腺X线造影的影像组学预测导管原位癌
Kun Zhang,Juan Qiu,Lijuan Wang et al.
Kun Zhang et al.
Our investigation focuses on developing and testing a radiomics nomogram based on contrast-enhanced mammography (CEM) and clinical factors to predict ductal carcinoma in situ (DCIS) in breast cancer. A retrospective analysis was performed o...
Development and Application of Automated Preoperative Planning System for Developmental Dysplasia of the Hip via Keypoint Selective Integration [0.03%]
基于关键点选择融合的髋关节发育不良术前规划系统的研发及应用研究
Jinghui Yao,Xiaoyou Fan,Yijian Wang et al.
Jinghui Yao et al.
This study developed and prospectively validated a deep learning-based automated preoperative planning system for developmental dysplasia of the hip (DDH) to guide osteotomy. Using 3544 anteroposterior pelvic radiographs, a selective keypoi...
Towards Explainability in Deep Learning for Detection of Five Major Intracranial Hemorrhage Subtypes on Head CT Using Multi-window DICOM Imaging and Patient-Level Cross-Validation [0.03%]
基于多窗口DICOM影像和患者级交叉验证的五类颅内出血检测的深度学习可解释性研究
H Sekkat,A El Haouat,O El Mouden et al.
H Sekkat et al.
Intracranial hemorrhage (ICH) is a time-critical neurologic emergency where delayed diagnosis can worsen outcomes. Non-contrast head CT is the first-line imaging modality, and explainable AI tools may enhance rapid detection and subtype cla...
Machine Learning Based on Multiparametric Features from Dual-Layer Detector Spectral CT for Identifying Ulcer-Like Projection in Aortic Intramural Hematoma [0.03%]
基于双层探测器CT多参数特征的机器学习在主动脉夹层血肿内膜下血肿判别中的应用
Qin Song,Yinzhen Li,Hui Duan et al.
Qin Song et al.
Aortic intramural hematoma (IMH) is a high-risk subtype of acute aortic syndrome (AAS). The presence of ulcer-like projection (ULP) significantly increases the risk of progression to dissection, aneurysm, or rupture. However, conventional c...
Comparative Study of Training Strategies for Projection-Domain Denoising in Multislice Helical CT [0.03%]
多层螺旋CT投影域去噪训练策略的比较研究
Zsolt Adam Balogh,Mahmoud Nizar Hassan,Mohammad Shahid et al.
Zsolt Adam Balogh et al.
Low-dose computed tomography (LDCT) is essential for reducing patient radiation exposure but often suffers from high noise and streak artifacts. The vast majority of publications on LDCT denoising focus on image-domain approaches. This is m...
A Scalable, Annotation-Free Pipeline for Automated CT Pelvimetry: A Validation Study with Landmark Uncertainty Analysis and Clinical Correlation [0.03%]
一种可扩展、无需标注的自动CT pelvimetry管道：具有地标不确定性分析和临床相关性的验证研究
Shih-Feng Huang,Hsin-Ping Tseng,Yu-Hsun Chen et al.
Shih-Feng Huang et al.
This study presents the validation of a fully automated, annotation-free CT pelvimetry pipeline that is built on a publicly available, interchangeable segmentation backend (here, TotalSegmentator) without task-specific retraining, derives s...
Improving Medical Diagnostics with Vision-Language Models: Convex Hull-Based Uncertainty Analysis [0.03%]
基于凸包的不确定性分析：用于改进医学诊断的视觉语言模型
Ferhat Ozgur Catak,Murat Kuzlu,Taylor Patrick et al.
Ferhat Ozgur Catak et al.
In recent years, vision-language models (VLMs) have been applied to various fields, including healthcare, education, finance, and manufacturing, with remarkable performance. However, concerns remain regarding VLMs' consistency and uncertain...
A Thyroid Nodule Differentiation Model for Benign-Malignant Identification by Fusing Transfer Learning and Gradient Boosting Decision Tree [0.03%]
基于迁移学习和梯度提升决策树融合的甲状腺结节良恶性鉴别模型
Bo Li,Tingxue Li,Hao Ju et al.
Bo Li et al.
Accurate identification of benign and malignant thyroid nodules is a core link in clinical diagnosis and treatment decision-making, which directly affects the selection of subsequent treatment plans for patients. Aiming at the problems such...
A Bounded Public DICOM Metadata Audit for UDI-DICOM Evidence Readiness in Medical Imaging Workflows [0.03%]
面向医疗成像工作流中UDI-DICOM证据准备性的有界公共DICOM元数据审计
Bin Zhang
Bin Zhang
The objective of this study is to assess whether selected public Digital Imaging and Communications in Medicine (DICOM) archive series contain archive-observable equipment-identity and Unique Device Identification (UDI)-related metadata nee...
Automated Body Composition from Computed Tomography Scans Improves Survival Prediction in Colorectal Cancer Patients [0.03%]
基于计算机断层扫描的自动化身体组成可改善结直肠癌患者的生存预测能力
Mushfiqus Salehin,Hyunwoo Lee,Vincent Tze Yang Chow et al.
Mushfiqus Salehin et al.
Colorectal cancer is one of the most common cancers, but the current staging system is limited by the variability and paradoxical survival outcomes. Body composition is an accurate predictor of survival and can be extracted from routine com...