Multispectral Imaging Method for Rapid Identification and Analysis of Paraffin-Embedded Pathological Tissues [0.03%]
石蜡包埋病理组织的快速识别与分析的多光谱成像方法
Ouafa Sijilmassi,José-Manuel López Alonso,Aurora Del Río Sevilla et al.
Ouafa Sijilmassi et al.
The study of the interaction between light and biological tissue is of great help in the identification of diseases as well as structural alterations in tissues. In the present study, we have developed a tissue diagnostic technique by using...
Evaluation of Image Quality and Detectability of Deep Learning Image Reconstruction (DLIR) Algorithm in Single- and Dual-energy CT [0.03%]
基于深度学习的单能量与双能量CT图像重建算法的图像质量及病变检测能力的评价研究
Jingyu Zhong,Hailin Shen,Yong Chen et al.
Jingyu Zhong et al.
This study is aimed to evaluate effects of deep learning image reconstruction (DLIR) on image quality in single-energy CT (SECT) and dual-energy CT (DECT), in reference to adaptive statistical iterative reconstruction-V (ASIR-V). The Gammex...
Pilot Lightweight Denoising Algorithm for Multiple Sclerosis on Spine MRI [0.03%]
一种脊髓多发性硬化症的轻量级去噪算法试点研究
John D Mayfield,Katie Bailey,Andrew A Borkowski et al.
John D Mayfield et al.
Multiple sclerosis (MS) is a severely debilitating disease which requires accurate and timely diagnosis. MRI is the primary diagnostic vehicle; however, it is susceptible to noise and artifact which can limit diagnostic accuracy. A myriad o...
CCS-GAN: COVID-19 CT Scan Generation and Classification with Very Few Positive Training Images [0.03%]
用于生成和分类新冠肺炎CT扫描的CCS-GAN算法
Sumeet Menon,Jayalakshmi Mangalagiri,Josh Galita et al.
Sumeet Menon et al.
We present a novel algorithm that is able to generate deep synthetic COVID-19 pneumonia CT scan slices using a very small sample of positive training images in tandem with a larger number of normal images. This generative algorithm produces...
DeepBLS: Deep Feature-Based Broad Learning System for Tissue Phenotyping in Colorectal Cancer WSIs [0.03%]
基于深度特征的广义学习系统：结直肠癌组织分型中的DeepBLS研究
Ahsan Baidar Bakht,Sajid Javed,Syed Qasim Gilani et al.
Ahsan Baidar Bakht et al.
Tissue phenotyping is a fundamental step in computational pathology for the analysis of tumor micro-environment in whole slide images (WSIs). Automatic tissue phenotyping in whole slide images (WSIs) of colorectal cancer (CRC) assists patho...
Evaluation of Semiautomatic and Deep Learning-Based Fully Automatic Segmentation Methods on [18F]FDG PET/CT Images from Patients with Lymphoma: Influence on Tumor Characterization [0.03%]
基于[18F]FDG PET/CT图像的半自动和深度学习的全自动化分割方法在淋巴瘤患者中的评估：对肿瘤特征化的影响
Cláudia S Constantino,Sónia Leocádio,Francisco P M Oliveira et al.
Cláudia S Constantino et al.
The objective is to assess the performance of seven semiautomatic and two fully automatic segmentation methods on [18F]FDG PET/CT lymphoma images and evaluate their influence on tumor quantification. All lymphoma lesions identified in 65 wh...
Post-revascularization Ejection Fraction Prediction for Patients Undergoing Percutaneous Coronary Intervention Based on Myocardial Perfusion SPECT Imaging Radiomics: a Preliminary Machine Learning Study [0.03%]
基于心肌灌注SPECT影像组学的经皮冠状动脉介入治疗术后左室射血分数预测：一项初步机器学习研究
Mobin Mohebi,Mehdi Amini,Mohammad Javad Alemzadeh-Ansari et al.
Mobin Mohebi et al.
In this study, the ability of radiomics features extracted from myocardial perfusion imaging with SPECT (MPI-SPECT) was investigated for the prediction of ejection fraction (EF) post-percutaneous coronary intervention (PCI) treatment. A tot...
Tensor-RT-Based Transfer Learning Model for Lung Cancer Classification [0.03%]
基于Tensor-RT的肺癌分类迁移学习模型
Vidhi Bishnoi,Nidhi Goel
Vidhi Bishnoi
Cancer is a leading cause of death across the globe, in which lung cancer constitutes the maximum mortality rate. Early diagnosis through computed tomography scan imaging helps to identify the stages of lung cancer. Several deep learning-ba...
The Keratectasia Volume (KEV) in Corneal Topography to Evaluate the Effect of Corneal Collagen Cross-linking in Pediatric Keratoconus [0.03%]
角膜地形图中角膜扩张体积（KERATECTASIA VOLUME，KEV）评价儿童圆锥角膜患者胶原交联疗效的影响
Xiangjun Wang,Bo Zhang,Zhiwei Li et al.
Xiangjun Wang et al.
The study aimed to evaluate the keratectasia volume (KEV) before and after corneal cross-linking (CXL) in pediatric patients. This study included 40 eyes of 25 pediatric patients (10-19 years) undergoing standard CXL. The support vector mac...
Comparison Between the Stereoscopic Virtual Reality Display System and Conventional Computed Tomography Workstation in the Diagnosis and Characterization of Cerebral Arteriovenous Malformations [0.03%]
立体虚拟显示系统与常规CT工作站诊断及定性脑动静脉畸形的比较研究
Xiujuan Liu,Jun Mao,Ning Sun et al.
Xiujuan Liu et al.
It is difficult to accurately understand the angioarchitecture of cerebral arteriovenous malformations (CAVMs) before surgery using existing imaging methods. This study aimed to evaluate the ability of the stereoscopic virtual reality displ...
Randomized Controlled Trial
Journal of digital imaging. 2023 Aug;36(4):1910-1918. DOI:10.1007/s10278-023-00807-y 2023