The Use of fMRI Regional Analysis to Automatically Detect ADHD Through a 3D CNN-Based Approach [0.03%]
基于三维卷积神经网络的ADHD自动检测方法及区域扫描分析
Perihan Gülşah Gülhan,Güzin Özmen
Perihan Gülşah Gülhan
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by a reduced attention span, hyperactivity, and impulsive behaviors, which typically manifest during childhood. This study employs functional mag...
Evaluating the Accuracy and Impact of the ESR-iGuide Decision Support Tool in Optimizing CT Imaging Referral Appropriateness [0.03%]
评估ESR-iGuide决策支持工具在优化CT影像转诊适宜性方面的准确性和影响
Osnat Luxenburg,Sharona Vaknin,Rachel Wilf-Miron et al.
Osnat Luxenburg et al.
Radiology referral quality impacts patient care, yet factors influencing quality are poorly understood. This study assessed the quality of computed tomography (CT) referrals, identified associated characteristics, and evaluated the ESR-iGui...
Policy Learning for Actively Labeled Sample Selection on Lumbar Semi-supervised Classification [0.03%]
主动标记样本选择的政策学习在腰椎半监督分类中的应用
Jinjin Hai,Jian Chen,Kai Qiao et al.
Jinjin Hai et al.
Large labeled data bring significant performance improvement, but acquiring labeled medical data is particularly challenging due to the laborious, time-consuming, and medically qualified annotation. Semi-supervised learning has been employe...
Enhanced Domain Adaptation for Foot Ulcer Segmentation Through Mixing Self-Trained Weak Labels [0.03%]
通过混合自训练弱标签改进域适应以进行足溃疡分割
David Jozef Hresko,Peter Drotar,Quoc Cuong Ngo et al.
David Jozef Hresko et al.
Wound management requires the measurement of the wound parameters such as its shape and area. However, computerized analysis of the wound suffers the challenge of inexact segmentation of the wound images due to limited or inaccurate labels....
Cutting Edge to Cutting Time: Can ChatGPT Improve the Radiologist's Reporting? [0.03%]
从尖端到节省时间：ChatGPT能否改善放射科医生的报告？
Rayan A Ahyad,Yasir Zaylaee,Tasneem Hassan et al.
Rayan A Ahyad et al.
Radiology-structured reports (SR) have many advantages over free text (FT), but the wide implementation of SR is still lagging. A powerful tool such as GPT-4 can address this issue. We aim to employ a web-based reporting tool powered by GPT...
Fully and Weakly Supervised Deep Learning for Meniscal Injury Classification, and Location Based on MRI [0.03%]
基于MRI的半月板损伤的完全和弱监督深度学习分类及定位
Kexin Jiang,Yuhan Xie,Xintao Zhang et al.
Kexin Jiang et al.
Meniscal injury is a common cause of knee joint pain and a precursor to knee osteoarthritis (KOA). The purpose of this study is to develop an automatic pipeline for meniscal injury classification and localization using fully and weakly supe...
Balancing Performance and Interpretability in Medical Image Analysis: Case study of Osteopenia [0.03%]
医学影像分析中性能与可解释性的权衡：骨质减少症的案例研究
Mateo Mikulić,Dominik Vičević,Eszter Nagy et al.
Mateo Mikulić et al.
Multiple studies within the medical field have highlighted the remarkable effectiveness of using convolutional neural networks for predicting medical conditions, sometimes even surpassing that of medical professionals. Despite their great p...
US & MR/CT Image Fusion with Markerless Skin Registration: A Proof of Concept [0.03%]
无标志物皮肤配准的US与MR/CT图像融合技术的概念验证研究
Martina Paccini,Giacomo Paschina,Stefano De Beni et al.
Martina Paccini et al.
This paper presents an innovative automatic fusion imaging system that combines 3D CT/MR images with real-time ultrasound acquisition. The system eliminates the need for external physical markers and complex training, making image fusion fe...
Metastatic Lung Adenocarcinomas: Development and Evaluation of Radiomic-Based Methods to Measure Baseline Intra-Patient Inter-Tumor Lesion Heterogeneity [0.03%]
基线水平肺癌患者体内病灶间异质性的影像组学测量及评价方法的建立和评估
Mathilde Lafon,Sophie Cousin,Mélissa Alamé et al.
Mathilde Lafon et al.
Radiomics has traditionally focused on individual tumors, often neglecting the integration of metastatic disease, particularly in patients with non-small cell lung cancer. This study sought to examine intra-patient inter-tumor lesion hetero...
Multi-parameter MRI-Based Machine Learning Model to Evaluate the Efficacy of STA-MCA Bypass Surgery for Moyamoya Disease: A Pilot Study [0.03%]
基于多参数MRI的机器学习模型评估STA-MCA旁路手术治疗 moyamoya 病疗效的价值：一项前瞻性研究
Huaizhen Wang,Jizhen Li,Jinming Chen et al.
Huaizhen Wang et al.
Superficial temporal artery-middle cerebral artery (STA-MCA) bypass surgery represents the primary treatment for Moyamoya disease (MMD), with its efficacy contingent upon collateral vessel development. This study aimed to develop and valida...