Dual Energy CT for Deep Learning-Based Segmentation and Volumetric Estimation of Early Ischemic Infarcts [0.03%]
基于双重能量CT的深度学习缺血性梗死分割及体积评估方法
Peter Kamel,Mazhar Khalid,Rachel Steger et al.
Peter Kamel et al.
Ischemic changes are not visible on non-contrast head CT until several hours after infarction, though deep convolutional neural networks have shown promise in the detection of subtle imaging findings. This study aims to assess if dual-energ...
Deep Conformal Supervision: Leveraging Intermediate Features for Robust Uncertainty Quantification [0.03%]
深度一致性监督：利用中间特征进行鲁棒不确定性量化
Amir M Vahdani,Shahriar Faghani
Amir M Vahdani
Trustworthiness is crucial for artificial intelligence (AI) models in clinical settings, and a fundamental aspect of trustworthy AI is uncertainty quantification (UQ). Conformal prediction as a robust uncertainty quantification (UQ) framewo...
Leveraging Ensemble Models and Follow-up Data for Accurate Prediction of mRS Scores from Radiomic Features of DSC-PWI Images [0.03%]
基于DSC-PWI影像的放射组学特征准确预测mRS评分的集成模型及随访数据利用方法研究
Mazen M Yassin,Asim Zaman,Jiaxi Lu et al.
Mazen M Yassin et al.
Predicting long-term clinical outcomes based on the early DSC PWI MRI scan is valuable for prognostication, resource management, clinical trials, and patient expectations. Current methods require subjective decisions about which imaging fea...
A Lightweight Method for Breast Cancer Detection Using Thermography Images with Optimized CNN Feature and Efficient Classification [0.03%]
基于优化CNN特征和高效分类的乳腺癌红外图像轻量级检测方法
Thanh Nguyen Chi,Hong Le Thi Thu,Tu Doan Quang et al.
Thanh Nguyen Chi et al.
Breast cancer is a prominent cause of death among women worldwide. Infrared thermography, due to its cost-effectiveness and non-ionizing radiation, has emerged as a promising tool for early breast cancer diagnosis. This article presents a h...
Automated Neural Architecture Search for Cardiac Amyloidosis Classification from [18F]-Florbetaben PET Images [0.03%]
基于[18F]氟斑比特PET图像自动神经体系结构搜索的心脏淀粉样变分类方法
Filippo Bargagna,Donato Zigrino,Lisa Anita De Santi et al.
Filippo Bargagna et al.
Medical image classification using convolutional neural networks (CNNs) is promising but often requires extensive manual tuning for optimal model definition. Neural architecture search (NAS) automates this process, reducing human interventi...
MobileNet-V2: An Enhanced Skin Disease Classification by Attention and Multi-Scale Features [0.03%]
改进的皮肤疾病分类方法：利用注意力机制和多尺度特征的MobileNet-V2网络
Nirupama,Virupakshappa
Nirupama
The increasing prevalence of skin diseases necessitates accurate and efficient diagnostic tools. This research introduces a novel skin disease classification model leveraging advanced deep learning techniques. The proposed architecture comb...
Ocular Imaging Challenges, Current State, and a Path to Interoperability: A HIMSS-SIIM Enterprise Imaging Community Whitepaper [0.03%]
眼科影像挑战、现状及互操作性路径：HIMSS-SIIM企业影像社区白皮书
Kerry E Goetz,Michael V Boland,Zhongdi Chu et al.
Kerry E Goetz et al.
Office-based testing, enhanced by advances in imaging technology, is routinely used in eye care to non-invasively assess ocular structure and function. This type of imaging coupled with autonomous artificial intelligence holds immense oppor...
A Robust [18F]-PSMA-1007 Radiomics Ensemble Model for Prostate Cancer Risk Stratification [0.03%]
一种稳健的[18F]-PSMA-1007前列腺癌风险分层影像组学模型
Giovanni Pasini,Alessandro Stefano,Cristina Mantarro et al.
Giovanni Pasini et al.
The aim of this study is to investigate the role of [18F]-PSMA-1007 PET in differentiating high- and low-risk prostate cancer (PCa) through a robust radiomics ensemble model. This retrospective study included 143 PCa patients who underwent ...
Deep Learning Approaches for Brain Tumor Detection and Classification Using MRI Images (2020 to 2024): A Systematic Review [0.03%]
基于MRI图像的脑肿瘤检测与分类的深度学习方法(2020至2024年)：系统性综述
Sara Bouhafra,Hassan El Bahi
Sara Bouhafra
Brain tumor is a type of disease caused by uncontrolled cell proliferation in the brain leading to serious health issues such as memory loss and motor impairment. Therefore, early diagnosis of brain tumors plays a crucial role to extend the...
Deep Learning Classification of Ischemic Stroke Territory on Diffusion-Weighted MRI: Added Value of Augmenting the Input with Image Transformations [0.03%]
基于扩散加权MRI的缺血性卒中供血区深度学习分类：通过图像变换增加输入带来的附加价值
Ilker Ozgur Koska,Alper Selver,Fazil Gelal et al.
Ilker Ozgur Koska et al.
Our primary aim with this study was to build a patient-level classifier for stroke territory in DWI using AI to facilitate fast triage of stroke to a dedicated stroke center. A retrospective collection of DWI images of 271 and 122 consecuti...