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pro vyhledávání: '"Li, Xiaomeng"'
Ordinal regression is a fundamental problem within the field of computer vision, with customised well-trained models on specific tasks. While pre-trained vision-language models (VLMs) have exhibited impressive performance on various vision tasks, the
Externí odkaz:
http://arxiv.org/abs/2408.03574
Autor:
Alberb, Muhammad, Elbatel, Marawan, Elgebaly, Aya, Montoya-del-Angel, Ricardo, Li, Xiaomeng, Martí, Robert
Digital Breast Tomosynthesis (DBT) is an advanced breast imaging modality that offers superior lesion detection accuracy compared to conventional mammography, albeit at the trade-off of longer reading time. Accelerating lesion detection from DBT usin
Externí odkaz:
http://arxiv.org/abs/2407.17620
Federated semi-supervised learning (FedSemi) refers to scenarios where there may be clients with fully labeled data, clients with partially labeled, and even fully unlabeled clients while preserving data privacy. However, challenges arise from client
Externí odkaz:
http://arxiv.org/abs/2407.10327
Accurate detection of bone fenestration and dehiscence (FD) is crucial for effective treatment planning in dentistry. While cone-beam computed tomography (CBCT) is the gold standard for evaluating FD, it comes with limitations such as radiation expos
Externí odkaz:
http://arxiv.org/abs/2407.09088
Semi-supervised medical image segmentation (SSMIS) has emerged as a promising solution to tackle the challenges of time-consuming manual labeling in the medical field. However, in practical scenarios, there are often domain variations within the data
Externí odkaz:
http://arxiv.org/abs/2407.07763
Generative modeling seeks to approximate the statistical properties of real data, enabling synthesis of new data that closely resembles the original distribution. Generative Adversarial Networks (GANs) and Denoising Diffusion Probabilistic Models (DD
Externí odkaz:
http://arxiv.org/abs/2407.03018
Cone-Beam Computed Tomography (CBCT) is an indispensable technique in medical imaging, yet the associated radiation exposure raises concerns in clinical practice. To mitigate these risks, sparse-view reconstruction has emerged as an essential researc
Externí odkaz:
http://arxiv.org/abs/2407.01090
Cone beam computed tomography (CBCT) is an important imaging technology widely used in medical scenarios, such as diagnosis and preoperative planning. Using fewer projection views to reconstruct CT, also known as sparse-view reconstruction, can reduc
Externí odkaz:
http://arxiv.org/abs/2406.03902
Autor:
Schmidt, Kendall, Bearce, Benjamin, Chang, Ken, Coombs, Laura, Farahani, Keyvan, Elbatele, Marawan, Mouhebe, Kaouther, Marti, Robert, Zhang, Ruipeng, Zhang, Yao, Wang, Yanfeng, Hu, Yaojun, Ying, Haochao, Xu, Yuyang, Testagrose, Conrad, Demirer, Mutlu, Gupta, Vikash, Akünal, Ünal, Bujotzek, Markus, Maier-Hein, Klaus H., Qin, Yi, Li, Xiaomeng, Kalpathy-Cramer, Jayashree, Roth, Holger R.
Publikováno v:
Medical Image Analysis Volume 95, July 2024, 103206
The correct interpretation of breast density is important in the assessment of breast cancer risk. AI has been shown capable of accurately predicting breast density, however, due to the differences in imaging characteristics across mammography system
Externí odkaz:
http://arxiv.org/abs/2405.14900
Radiology report generation aims to automatically generate detailed and coherent descriptive reports alongside radiology images. Previous work mainly focused on refining fine-grained image features or leveraging external knowledge. However, the preci
Externí odkaz:
http://arxiv.org/abs/2405.00962