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期刊名:Medical image analysis

缩写:MED IMAGE ANAL

ISSN:1361-8415

e-ISSN:1361-8423

IF/分区:11.8/Q1

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共收录本刊相关文章索引3113
Clinical Trial Case Reports Meta-Analysis RCT Review Systematic Review
Classical Article Case Reports Clinical Study Clinical Trial Clinical Trial Protocol Comment Comparative Study Editorial Guideline Letter Meta-Analysis Multicenter Study Observational Study Randomized Controlled Trial Review Systematic Review
Patrick Fuhlert,Fabian Westhaeusser,Esther Dietrich et al. Patrick Fuhlert et al.
The histopathological evaluation of biopsies by human experts is a gold standard in clinical disease diagnosis. While recent artificial intelligence-based (AI) approaches have reached human expert-level performance, they often display short...
Fanhao Qiu,Yangyang Zhang,Zhen-Li Huang et al. Fanhao Qiu et al.
Virtual immunohistochemistry (IHC) staining automatically translates Hematoxylin and Eosin (H&E) images into IHC images using deep generative models, enabling automation of IHC staining. Weakly supervised methods for virtual IHC staining le...
Mingyuan Liu,Lu Xu,Yuzhuo Gu et al. Mingyuan Liu et al.
Unlike the prevalent image classification paradigm that assumes all samples belong to pre-defined classes, Open set recognition (OSR) indicates that new classes unobserved during training could appear in testing. It mandates a model to not ...
Qibiao Wu,Yagang Wang,Qian Zhang Qibiao Wu
Manual annotation of airway regions in computed tomography images is a time-consuming and expertise-dependent task. Automatic airway segmentation is therefore a prerequisite for enabling rapid bronchoscopic navigation and the clinical deplo...
Tim J M Jaspers,Ronald L P D de Jong,Yiping Li et al. Tim J M Jaspers et al.
Foundation models have revolutionized computer vision by achieving vastly superior performance across diverse tasks through large-scale pretraining on extensive datasets. However, their application in surgical computer vision has been limit...
Haiqiao Wang,Zhuoyuan Wang,Dong Ni et al. Haiqiao Wang et al.
Deformable image registration plays a crucial role in medical imaging, aiding in disease diagnosis and image-guided interventions. Traditional iterative methods are slow, while deep learning (DL) accelerates solutions but faces usability an...
Zhiqiang Shen,Peng Cao,Junming Su et al. Zhiqiang Shen et al.
Mix-up is a key technique for consistency regularization-based semi-supervised learning methods, blending two or more images to generate strong-perturbed samples for strong-weak pseudo supervision. Existing mix-up operations are performed e...
Weiran Xia,Xin Zhang,Dan Hu et al. Weiran Xia et al.
Brain functional connectivity (FC) constructed from resting-state functional MRI (rs-fMRI) is the predominant method for studying brain functional organization of infants. Predicting the full dynamic developmental trajectory of infant FC fr...
Lintao Zhang,Mengqi Wu,Lihong Wang et al. Lintao Zhang et al.
Image noise and motion artifacts greatly affect the quality of brain magnetic resonance imaging (MRI) and negatively influence downstream medical image analysis. Previous studies often focus on 2D methods that process each volumetric MR ima...
Baoshun Shi,Bing Chen,Shaolei Zhang et al. Baoshun Shi et al.
Low-dose CT (LDCT) is capable of reducing X-ray radiation exposure, but it will potentially degrade image quality, even yields metal artifacts at the case of metallic implants. For simultaneous LDCT reconstruction and metal artifact reducti...