Multidimensional Comparisons Between Constrained ICA/IVA Algorithms for Multi-Subject fMRI Data Analysis [0.03%]
基于约束的ICA/IVA算法在多被试fMRI数据分析中的多维度比较研究
Lucas Gois,Hanlu Yang,Trung Vu et al.
Lucas Gois et al.
Large-scale functional magnetic resonance imaging (fMRI) datasets provide exciting opportunities for understanding and improving brain health. Data-driven techniques such as independent component analysis (ICA) and independent vector analys...
ID-GBA: Subgraph Extension With Information Distance Guilt by Association in Complex Networks [0.03%]
基于复杂网络中信息距离的Guilt By Association的子图扩展算法
Predrag Obradovic,Vladimir Kovacevic,Aleksandar Milosavljevic et al.
Predrag Obradovic et al.
Here, we introduce the ID-GBA (Information Distance Guilt By Association) method to expand highly connected sets of nodes by deploying a novel algorithm for subgraph extension based on the guilt-by-association principle and information dist...
A Numerical Comparison of Petri Net and Ordinary Differential Equation SIR Component Models [0.03%]
基于Petri网和常微分方程的SIR模型的数值比较
Trevor Reckell,Bright Kwaku Manu,Beckett Sterner et al.
Trevor Reckell et al.
Petri nets are an increasingly used modeling framework for the spread of disease across populations or within an individual. For example, the Susceptible-Infectious-Recovered (SIR) compartment model is foundational for population epidemiolo...
Automatic Explainable Segmentation of Abdominal Aortic Aneurysm From Computed Tomography Angiography [0.03%]
基于CTA的腹主动脉瘤自动可解释分割方法
Merjulah Roby,Abu Noman Md Sakib,Zijie Zhang et al.
Merjulah Roby et al.
This work presents an automated deep learning (DL) based framework for segmenting abdominal aortic aneurysm (AAA) in contrast-enhanced computed tomography angiography (CTA) images, which was developed to support AAA screening and analysis. ...
Guangzong Chen,Mingui Sun,Zhi-Hong Mao et al.
Guangzong Chen et al.
Existing image-to-image translation models often rely on complex architectures with multiple loss terms, making them difficult to interpret and computationally expensive. This paper is motivated by the need for a simpler, more fundamental u...
Developing a Deep Learning Approach for Automated Body Composition Prediction in Newborns Using Ultrasound Images [0.03%]
基于超声图像的新生儿自动身体成分预测的深度学习方法研究
Keshi He,Y I Li,Hayoung Cho et al.
Keshi He et al.
Objective: Measurements of human body composition such as fat mass (FM) and fat-free mass (FFM) are critical for studying malnutrition and the effects of nutritional interventions. This study introduces research toward a ...
From CNNs to SAM: A Survey of Deep Learning Techniques for Liver Tumor Segmentation in CT Images [0.03%]
从CNN到SAM：CT图像中肝脏肿瘤分割的深度学习方法综述
Neman Abdoli,Youkabed Sadri,Patrik Gilley et al.
Neman Abdoli et al.
Accurate liver tumor segmentation is a critical component of clinical assessment, forming the basis for treatment planning, therapy response monitoring, prognostic assessment, and the delivery of precision medicine. However, in real-world c...
Topology Assisted Clustering of Temporal fMRI Brain Networks With Use-Case in Mitigating Non-Neural Multi-Site Variability [0.03%]
基于拓扑的时变fMRI脑网络聚类及其在消除非神经多重站点差异中的应用研究
Ahmedur Rahman Shovon,Sidharth Kumar,Gopikrishna Deshpande
Ahmedur Rahman Shovon
Using temporal analysis of fMRI (functional Magnetic Resonance Imaging) data, we can characterize dynamic changes in brain connectivity over time. However, dynamic temporal analysis of fMRI data is challenging due to the high dimensionality...
Low-Cost and Fast Epiretinal Membrane Detection and Quantification Based on SD-OCT [0.03%]
基于SD-OCT的低成本和快速视网膜前膜检测与量化方法
Seungju Baek,Insup Lee,Kuk Jin Jang et al.
Seungju Baek et al.
Epiretinal membrane (ERM) is a pathological condition characterized by the formation of a non-vascularized fibrocellular membrane on the inner retinal surface, leading to retinal traction, macular edema, and visual impairment. Optical coher...
XAPT: Explainable Anomaly-Driven Prediction of Threat Stages in APT Campaigns [0.03%]
基于异常的APT威胁阶段攻击预测模型及其可解释性研究
Wei Lu,Issa Traoré,Isaac Woungang et al.
Wei Lu et al.
Advanced Persistent Threats (APTs) are long-lived, targeted cyberattacks that progress through multiple stages, characterized by strong stealth and intent. To achieve accurate and interpretable stage-level prediction, we propose XAPT, an eX...