Performance of A Statistical-Based Automatic Contrast-to-Noise Ratio Measurement on Images of the ACR CT Phantom [0.03%]
基于统计的ACR CT模体图像自动对比度噪声比测量方法性能研究
Choirul Anam,Riska Amilia,Ariij Naufal et al.
Choirul Anam et al.
This study evaluates the performance of a statistical-based automatic contrast-to-noise ratio (CNR) measurement method on images of the ACR CT phantom under varying imaging parameters. A statistical automatic method for segmenting low-contr...
CAS-SFCM: Content-Aware Image Smoothing Based on Fuzzy Clustering with Spatial Information [0.03%]
基于空间信息的模糊聚类的内容感知图像平滑算法
Felipe Antunes-Santos,Carlos Lopez-Molina,Maite Mendioroz et al.
Felipe Antunes-Santos et al.
Image smoothing is a low-level image processing task mainly aimed at homogenizing an image, mitigating noise, or improving the visibility of certain image areas. There exist two main strategies for image smoothing. The first strategy is con...
Javier Montalvo,Álvaro García-Martín,Pablo Carballeira et al.
Javier Montalvo et al.
Semantic segmentation is a computer vision task where classification is performed at the pixel level. Due to this, the process of labeling images for semantic segmentation is time-consuming and expensive. To mitigate this cost there has bee...
IEWNet: Multi-Scale Robust Watermarking Network Against Infrared Image Enhancement Attacks [0.03%]
鲁棒红外图像增强攻击的多尺度信息隐藏网络
Yu Bai,Li Li,Shanqing Zhang et al.
Yu Bai et al.
Infrared (IR) images record the temperature radiation distribution of the object being captured. The hue and color difference in the image reflect the caloric and temperature difference, respectively. However, due to the thermal diffusion e...
Three-Blind Validation Strategy of Deep Learning Models for Image Segmentation [0.03%]
深度学习模型在图像分割中的三盲验证策略
Andrés Larroza,Francisco Javier Pérez-Benito,Raquel Tendero et al.
Andrés Larroza et al.
Image segmentation plays a central role in computer vision applications such as medical imaging, industrial inspection, and environmental monitoring. However, evaluating segmentation performance can be particularly challenging when ground t...
Recovery and Characterization of Tissue Properties from Magnetic Resonance Fingerprinting with Exchange [0.03%]
基于磁共振指纹图谱的交换模型的数据重建与特性分析方法研究
Naren Nallapareddy,Soumya Ray
Naren Nallapareddy
Magnetic resonance fingerprinting (MRF), a quantitative MRI technique, enables the acquisition of multiple tissue properties in a single scan. In this paper, we study a proposed extension of MRF, MRF with exchange (MRF-X), which can enable ...
The Creation of Artificial Data for Training a Neural Network Using the Example of a Conveyor Production Line for Flooring [0.03%]
基于地板输送生产线示例的神经网络训练用人工数据集生成方法研究
Alexey Zaripov,Roman Kulshin,Anatoly Sidorov
Alexey Zaripov
This work is dedicated to the development of a system for generating artificial data for training neural networks used within a conveyor-based technology framework. It presents an overview of the application areas of computer vision (CV) an...
Comparing Geodesic Filtering to State-of-the-Art Algorithms: A Comprehensive Study and CUDA Implementation [0.03%]
几何滤波与最新算法比较：全面研究及CUDA实现
Pierre Boulanger,Sadid Bin Hasan
Pierre Boulanger
This paper presents a comprehensive investigation into advanced image processing using geodesic filtering within a Riemannian manifold framework. We introduce a novel geodesic filtering formulation that uniquely integrates spatial and inten...
"ShapeNet": A Shape Regression Convolutional Neural Network Ensemble Applied to the Segmentation of the Left Ventricle in Echocardiography [0.03%]
“形变网络”：一种应用于超声心动图中左心室分割的形状回归卷积神经网络集合
Eduardo Galicia Gómez,Fabián Torres-Robles,Jorge Perez-Gonzalez et al.
Eduardo Galicia Gómez et al.
Left ventricle (LV) segmentation is crucial for cardiac diagnosis but remains challenging in echocardiography. We present ShapeNet, a fully automatic method combining a convolutional neural network (CNN) ensemble with an improved active sha...
Segmentation of Non-Small Cell Lung Carcinomas: Introducing DRU-Net and Multi-Lens Distortion [0.03%]
非小细胞肺癌的分割：DRU-Net和多镜头畸变技术介绍
Soroush Oskouei,Marit Valla,André Pedersen et al.
Soroush Oskouei et al.
The increased workload in pathology laboratories today means automated tools such as artificial intelligence models can be useful, helping pathologists with their tasks. In this paper, we propose a segmentation model (DRU-Net) that can prov...