Developing a Reproducible Radiomics Model for Diagnosis of Active Crohn's Disease on CT Enterography Across Annotation Variations and Acquisition Differences [0.03%]
一种可重复的放射组学模型用于CT回肠造影活动性克罗恩病诊断跨越标注差异和获取差异的方法
Prathyush V Chirra,Pavithran Giriprakash,Alain G Rizk et al.
Prathyush V Chirra et al.
To systematically identify radiomics features on CT enterography (CTE) scans which can accurately diagnose active Crohn's disease across multiple sources of variation. Retrospective study of CTE scans curated between 2013 and 2015, comprisi...
Comparative Bladder Cancer Tissues Prediction Using Vision Transformer [0.03%]
基于视觉Transformer的比较膀胱癌组织预测方法
Kubilay Muhammed Sunnetci,Faruk Enes Oguz,Mahmut Nedim Ekersular et al.
Kubilay Muhammed Sunnetci et al.
Bladder cancer, often asymptomatic in the early stages, is a type of cancer where early detection is crucial. Herein, endoscopic images are meticulously evaluated by experts, and sometimes even by different disciplines, to identify tissue t...
Utilizing Pseudo Color Image to Improve the Performance of Deep Transfer Learning-Based Computer-Aided Diagnosis Schemes in Breast Mass Classification [0.03%]
利用伪彩色图像提升基于深度迁移学习的乳腺肿块分类计算机辅助诊断性能
Meredith A Jones,Ke Zhang,Rowzat Faiz et al.
Meredith A Jones et al.
The purpose of this study is to investigate the impact of using morphological information in classifying suspicious breast lesions. The widespread use of deep transfer learning can significantly improve the performance of the mammogram base...
Ultra-High-Resolution Photon-Counting Detector CT Benefits Visualization of Abdominal Arteries: A Comparison to Standard-Reconstruction [0.03%]
超高分辨率单光子计数探测器CT对腹部动脉的血管成像优势：与常规重建比较
Huan Zhang,Yue Xing,Lingyun Wang et al.
Huan Zhang et al.
This study aimed to investigate the potential benefit of ultra-high-resolution (UHR) photon-counting detector CT (PCD-CT) angiography in visualization of abdominal arteries in comparison to standard-reconstruction (SR) images of virtual mon...
Integrating VAI-Assisted Quantified CXRs and Multimodal Data to Assess the Risk of Mortality [0.03%]
结合VAI辅助量化CXRs和多模态数据以评估死亡风险
Yu-Cheng Chen,Wen-Hui Fang,Chin-Sheng Lin et al.
Yu-Cheng Chen et al.
To address the unmet need for a widely available examination for mortality prediction, this study developed a foundation visual artificial intelligence (VAI) to enhance mortality risk stratification using chest X-rays (CXRs). The VAI employ...
Deep Learning Segmentation of Chromogenic Dye RNAscope From Breast Cancer Tissue [0.03%]
基于深度学习的染色RNA_SCOPE信号在乳腺肿瘤组织切片中的分割算法研究
Andrew Davidson,Arthur Morley-Bunker,George Wiggins et al.
Andrew Davidson et al.
RNAscope staining of breast cancer tissue allows pathologists to deduce genetic characteristics of the cancer by inspection at the microscopic level, which can lead to better diagnosis and treatment. Chromogenic RNAscope staining is easy to...
Correction: Checklist for Reproducibility of Deep Learning in Medical Imaging [0.03%]
关于可重复性清单在医学影像深度学习中的 Correction
Mana Moassefi,Yashbir Singh,Gian Marco Conte et al.
Mana Moassefi et al.
Published Erratum
Journal of imaging informatics in medicine. 2024 Oct 22. DOI:10.1007/s10278-024-01295-4 2024
Knee Osteoarthritis SCAENet: Adaptive Knee Osteoarthritis Severity Assessment Using Spatial Separable Convolution with Attention-Based Ensemble Networks with Hybrid Optimization Strategy [0.03%]
基于注意力的集成网络利用空间可分离卷积自适应评估膝关节骨关节炎严重程度(SCAENet)
Sriramulu Devarapaga,Rajesh Thumma
Sriramulu Devarapaga
Osteoarthritis (OA) of the knee is a chronic state that significantly lowers the quality of life for its patients. Early detection and lifetime monitoring of the progression of OA are necessary for preventive therapy. In the course of thera...
Foundational Segmentation Models and Clinical Data Mining Enable Accurate Computer Vision for Lung Cancer [0.03%]
基础分割模型和临床数据挖掘可实现准确的肺癌计算机视觉技术
Nathaniel C Swinburne,Christopher B Jackson,Andrew M Pagano et al.
Nathaniel C Swinburne et al.
This study aims to assess the effectiveness of integrating Segment Anything Model (SAM) and its variant MedSAM into the automated mining, object detection, and segmentation (MODS) methodology for developing robust lung cancer detection and ...
Addressing Challenges in Skin Cancer Diagnosis: A Convolutional Swin Transformer Approach [0.03%]
皮肤癌诊断中的挑战及基于卷积Swin变换器的方法
Sudha Paraddy,Virupakshappa
Sudha Paraddy
Skin cancer is one of the top three hazardous cancer types, and it is caused by the abnormal proliferation of tumor cells. Diagnosing skin cancer accurately and early is crucial for saving patients' lives. However, it is a challenging task ...