Bayesian Convolutional Neural Networks in Medical Imaging Classification: A Promising Solution for Deep Learning Limits in Data Scarcity Scenarios [0.03%]
面向数据稀疏场景的医学图像分类中的贝叶斯卷积神经网络研究
Filippo Bargagna,Lisa Anita De Santi,Nicola Martini et al.
Filippo Bargagna et al.
Deep neural networks (DNNs) have already impacted the field of medicine in data analysis, classification, and image processing. Unfortunately, their performance is drastically reduced when datasets are scarce in nature (e.g., rare diseases ...
Detecting and Characterizing Inferior Vena Cava Filters on Abdominal Computed Tomography with Data-Driven Computational Frameworks [0.03%]
基于数据驱动的计算框架检测和表征腹部CT扫描中的下腔静脉滤器
Sema Candemir,Robert Moranville,Kelvin A Wong et al.
Sema Candemir et al.
Two data-driven algorithms were developed for detecting and characterizing Inferior Vena Cava (IVC) filters on abdominal computed tomography to assist healthcare providers with the appropriate management of these devices to decrease complic...
DMCA-GAN: Dual Multilevel Constrained Attention GAN for MRI-Based Hippocampus Segmentation [0.03%]
基于MRI的海马分割的双重多级约束注意GAN（DMCA-GAN）
Xue Chen,Yanjun Peng,Dapeng Li et al.
Xue Chen et al.
Precise segmentation of the hippocampus is essential for various human brain activity and neurological disorder studies. To overcome the small size of the hippocampus and the low contrast of MR images, a dual multilevel constrained attentio...
Left Ventricular Myocardial Dysfunction Evaluation in Thalassemia Patients Using Echocardiographic Radiomic Features and Machine Learning Algorithms [0.03%]
应用超声心动图影像组学特征和机器学习算法评估地中海贫血患者左心室心肌功能障碍
Haniyeh Taleie,Ghasem Hajianfar,Maziar Sabouri et al.
Haniyeh Taleie et al.
Heart failure caused by iron deposits in the myocardium is the primary cause of mortality in beta-thalassemia major patients. Cardiac magnetic resonance imaging (CMRI) T2* is the primary screening technique used to detect myocardial iron ov...
Public Imaging Datasets of Gastrointestinal Endoscopy for Artificial Intelligence: a Review [0.03%]
胃肠内镜人工智能公共影像数据库综述
Shiqi Zhu,Jingwen Gao,Lu Liu et al.
Shiqi Zhu et al.
With the advances in endoscopic technologies and artificial intelligence, a large number of endoscopic imaging datasets have been made public to researchers around the world. This study aims to review and introduce these datasets. An extens...
External Validation of Robust Radiomic Signature to Predict 2-Year Overall Survival in Non-Small-Cell Lung Cancer [0.03%]
非小细胞肺癌患者2年总体生存率的放射组学标志物预测模型的外部验证研究
Ashish Kumar Jha,Umeshkumar B Sherkhane,Sneha Mthun et al.
Ashish Kumar Jha et al.
Lung cancer is the second most fatal disease worldwide. In the last few years, radiomics is being explored to develop prediction models for various clinical endpoints in lung cancer. However, the robustness of radiomic features is under que...
Correction to: The FIND Program: Improving Follow-up of Incidental Imaging Findings [0.03%]
补遗：FIND项目：提高偶然影像发现的追踪效率
Kaitlin M Zaki-Metias,Jeffrey J MacLean,Alexander M Satei et al.
Kaitlin M Zaki-Metias et al.
Published Erratum
Journal of digital imaging. 2023 Dec;36(6):2662-2663. DOI:10.1007/s10278-023-00898-7 2023
MF-Net: Automated Muscle Fiber Segmentation From Immunofluorescence Images Using a Local-Global Feature Fusion Network [0.03%]
基于局部全局特征融合网络的肌肉纤维免疫荧光图像自动化分割方法(MF-Net)
Getao Du,Peng Zhang,Jianzhong Guo et al.
Getao Du et al.
Histological assessment of skeletal muscle slices is very important for the accurate evaluation of weightless muscle atrophy. The accurate identification and segmentation of muscle fiber boundary is an important prerequisite for the evaluat...
Pulmonary Surface Irregularity Score as a New Quantitative CT Marker for Idiopathic Pulmonary Fibrosis-a Pilot Study [0.03%]
特发性肺纤维化的新型定量CT标记-肺表面不规则积分：一项初步研究
Asser M Abou Elkassem,Rafah Mresh,Ahmed Farag et al.
Asser M Abou Elkassem et al.
The purpose of this study is to evaluate the accuracy and inter-observer agreement of a quantitative pulmonary surface irregularity (PSI) score on high-resolution chest CT (HRCT) for predicting transplant-free survival in patients with IPF....
Deep Transfer Learning-Based Approach for Glucose Transporter-1 (GLUT1) Expression Assessment [0.03%]
基于深度迁移学习的葡萄糖转运蛋白-1(GLUT1)表达评估方法
Maisun Mohamed Al Zorgani,Hassan Ugail,Klaus Pors et al.
Maisun Mohamed Al Zorgani et al.
Glucose transporter-1 (GLUT-1) expression level is a biomarker of tumour hypoxia condition in immunohistochemistry (IHC)-stained images. Thus, the GLUT-1 scoring is a routine procedure currently employed for predicting tumour hypoxia marker...