An Automated Classification of Brain White Matter Inherited Disorders (Leukodystrophy) Using MRI Image Features [0.03%]
基于MRI图像特征的自动分类脑白质遗传性疾病(髓鞘溶解症)的方法
Zahra Seraji,Saeid Rashidi,Morteza Heidari et al.
Zahra Seraji et al.
Leukodystrophies are a group of inherited disorders that predominantly and selectively affect the white matter of the central nervous system. Their overlapping clinical and imaging manifestations make a timely and accurate diagnosis challen...
Towards Interpretable and Edge-Intelligent Masseter Monitoring: A Self-Powered Framework for On-Device and Continuous Assessment [0.03%]
面向解释性和边缘智能咬肌监测的自供电框架实现设备内连续评估的方法研究
Boyu Li,Xingchun Zhu,Yonghui Wu
Boyu Li
Continuous and interpretable monitoring of masseter muscle activity is essential for the assessment of sleep bruxism (SB) and temporomandibular dysfunction (TMD). However, existing surface electromyography (sEMG) systems remain constrained ...
Evaluating the Robustness of Dosiomics Features Over Treatment Planning Parameters: A Phantom-Based Study [0.03%]
基于体模的剂量组学特征评估：治疗计划参数下的稳健性研究
Mostafa Rezaei,Abbas Haghparast,Khadijah Hosseini et al.
Mostafa Rezaei et al.
Abstract

Dosimetric biomarkers, in terms of dosiomics features, play a crucial role in modeling radiotherapy and should be analyze d for their robustness and stability. This study aims to investigate how these dosiomics features wi...
Hybrid Radiomic-HOG Ensemble Model for Accurate Pulmonary Nodule Diagnosis [0.03%]
基于混合型纹理和HOG特征的肺结节影像诊断模型研究
Jiddu Krishnan O P,Pinki Roy
Jiddu Krishnan O P
Lung cancer remains one of the deadliest forms of cancer worldwide, making early and accurate pulmonary-nodule classification essential for improving patient prognosis. This study presents a robust ensemble-stacking framework that integrate...
Enhancing Lumbar Disc Herniation Classification through Region-of-Interest Guidance and Geometric Shape Features [0.03%]
基于兴趣区指导和几何形状特征的腰椎间盘突出症分类增强方法
Cong Zhang,Kunjin He,Wei Xu et al.
Cong Zhang et al.
Lumbar disc herniation (LDH) is one of the most common degenerative diseases of the spine. Magnetic resonance image is the most effective way to detect LDH. The variety of shapes and blurred boundaries of diseased discs, along with the uncl...
Metaheuristic-optimized generative adversarial network for enhanced sparse-view low-dose CT reconstruction [0.03%]
基于元启发式优化的生成对抗网络在稀疏低剂量CT重建中的应用研究
Jafar Majidpour,Hakem Beitollahi
Jafar Majidpour
Sparse-view low-dose computed tomography (LDCT) imaging poses difficulties in preserving image quality while reducing radiation exposure. Recent research has focused extensively on artificial intelligence (AI) to reduce artifacts in LDCT. T...
Upconversion nanoparticle-mediated targeted drug delivery and photodynamic therapy for enhanced lung cancer treatment [0.03%]
上转换纳米粒子介导的肺癌治疗增强型靶向药物输送和光动力疗法
Zamrood A Othman,Yousif M Hassan,Abdulkarim Y Karim
Zamrood A Othman
The uncontrolled release of pharmaceuticals in traditional drug delivery systems has resulted in the development of innovative drug delivery methods based on nanotechnology and the use of tailored nanocarriers for cancer treatment. This stu...
Design of a grid-patterned cuvette for in vitro studies of low-impedance biological samples using nanosecond pulsed electric fields [0.03%]
一种用于体外低阻抗生物样本纳秒脉冲电场实验的网格型比色皿的设计
Wen Dang,Yasir Alfadhl,Max Munoz Torricov et al.
Wen Dang et al.
Nanosecond pulsed electric fields (nsPEFs) have emerged as a promising modality for cancer treatment by inducing targeted immune responses. In in vitro studies, commercial cuvettes with narrow 1-mm gaps are typically employed to deliver hig...
Towards real-time non-invasive detection of hyperlipidemia through finger pulse image analysis using deep learning [0.03%]
基于深度学习的指尖脉象图像分析的实时高血脂无创检测方法研究
Hiruni Gunathilaka,Rumesh Rajapaksha,Thosini Kumarika et al.
Hiruni Gunathilaka et al.
Hyperlipidemia detection involves invasive, time-consuming procedures requiring clinical laboratories and blood samples. Often asymptomatic in its early stages, hyperlipidemia significantly increases the risk of cardiovascular diseases. The...
OCTSeg-UNeXt: An ultralight hybrid Conv-MLP network for retinal pathology segmentation in point-of-care OCT imaging [0.03%]
OCTSeg-UNeXt：一种用于护理点OCT成像视网膜病理分割的超轻量级混合Conv-MLP网络
Shujun Men,Jiamin Wang,Yanke Li et al.
Shujun Men et al.
To enable efficient and accurate retinal lesion segmentation on resource-constrained point-of-care Optical Coherence Tomography (OCT) systems, we propose OCTSeg-UNeXt, an ultralight hybrid Convolution-Multilayer Perceptron (Conv-MLP) networ...