Wannakamon Panyarak,Kittichai Wantanajittikul,Arnon Charuakkra et al.
Wannakamon Panyarak et al.
The study aimed to evaluate the impact of image size, area of detection (IoU) thresholds and confidence thresholds on the performance of the YOLO models in the detection of dental caries in bitewing radiographs. A total of 2575 bitewing rad...
Improving Image Classification of Knee Radiographs: An Automated Image Labeling Approach [0.03%]
改进膝部X光影像分类：一种自动影像标记方法
Jikai Zhang,Carlos Santos,Christine Park et al.
Jikai Zhang et al.
Large numbers of radiographic images are available in musculoskeletal radiology practices which could be used for training of deep learning models for diagnosis of knee abnormalities. However, those images do not typically contain readily a...
Hamidreza Ghaderi,Alain April
Hamidreza Ghaderi
Medical imaging technology is producing a growing number of medical images types as well as patient-related information. The benefits of using modern medical imaging systems in healthcare are undeniable. Picture archiving and communication ...
A Deep Learning Image Reconstruction Algorithm for Improving Image Quality and Hepatic Lesion Detectability in Abdominal Dual-Energy Computed Tomography: Preliminary Results [0.03%]
一种用于改善腹部分能CT图像质量和肝部病变检测的深度学习图像重建算法：初步结果
Bingqian Chu,Lu Gan,Yi Shen et al.
Bingqian Chu et al.
This study aimed to compare the performance of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-Veo (ASIR-V) in improving image quality and diagnostic performance using virtual monochromatic spectr...
Improving the Efficacy of ACR TI-RADS Through Deep Learning-Based Descriptor Augmentation [0.03%]
基于深度学习的描述符增强改进ACR TI-RADS的有效性
Lev Barinov,Ajit Jairaj,William D Middleton et al.
Lev Barinov et al.
Thyroid nodules occur in up to 68% of people, 95% of which are benign. Of the 5% of malignant nodules, many would not result in symptoms or death, yet 600,000 FNAs are still performed annually, with a PPV of 5-7% (up to 30%). Artificial int...
Diagnostic Value of MRI Features in Dual-phenotype Hepatocellular Carcinoma: A Preliminary Study [0.03%]
双表型肝细胞癌的磁共振诊断价值：初步研究
Hong-Xian Gu,Xiao-Shan Huang,Jian-Xia Xu et al.
Hong-Xian Gu et al.
This study aimed to explore the magnetic resonance imaging (MRI) features of dual-phenotype hepatocellular carcinoma (DPHCC) and their diagnostic value.The data of 208 patients with primary liver cancer were retrospectively analysed between...
Are the Pilots Onboard? Equipping Radiologists for Clinical Implementation of AI [0.03%]
乘员就位：放射科医师的人工智能临床应用准备技能培训
Umber Shafique,Umar Shafique Chaudhry,Alexander J Towbin
Umber Shafique
The incorporation of artificial intelligence into radiological clinical workflow is on the verge of being realized. To ensure that these tools are effective, measures must be taken to educate radiologists on tool performance and failure mod...
CT-based Radiogenomics Framework for COVID-19 Using ACE2 Imaging Representations [0.03%]
基于CT的用于COVID-19的放射基因组学框架（使用ACE2成像表征）
Tian Xia,Xiaohang Fu,Michael Fulham et al.
Tian Xia et al.
Coronavirus disease 2019 (COVID-19) is caused by Severe Acute Respiratory Syndrome Coronavirus 2 which enters the body via the angiotensin-converting enzyme 2 (ACE2) and altering its gene expression. Altered ACE2 plays a crucial role in the...
Applicability Evaluation of Full-Reference Image Quality Assessment Methods for Computed Tomography Images [0.03%]
全面参考图像质量评估方法在CT图像中适用性评价
Kohei Ohashi,Yukihiro Nagatani,Makoto Yoshigoe et al.
Kohei Ohashi et al.
Image quality assessments (IQA) are an important task for providing appropriate medical care. Full-reference IQA (FR-IQA) methods, such as peak signal-to-noise ratio (PSNR) and structural similarity (SSIM), are often used to evaluate imagin...
PFP-HOG: Pyramid and Fixed-Size Patch-Based HOG Technique for Automated Brain Abnormality Classification with MRI [0.03%]
基于金字塔和固定大小补丁的HOG技术，用于MRI的大脑异常自动分类方法
Ela Kaplan,Wai Yee Chan,Hasan Baki Altinsoy et al.
Ela Kaplan et al.
Detecting neurological abnormalities such as brain tumors and Alzheimer's disease (AD) using magnetic resonance imaging (MRI) images is an important research topic in the literature. Numerous machine learning models have been used to detect...