AIMC Topic: Diagnostic Imaging

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UPMatch: Enhancing Semi-Supervised Medical Image Classification through Contrastive Learning with Unreliable Pseudo Labels.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Pseudo-labeling based semi-supervised learning (SSL) framework has proven highly successful in medical image analysis (MIA) by addressing the problem of a shortage of labeled samples. However, the existing SSL methods use a fixed or flexible confiden...

Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update.

Radiology. Artificial intelligence
To address the rapid evolution of artificial intelligence in medical imaging, the authors present the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) 2024 Update.

Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges.

Radiology. Artificial intelligence
The Radiological Society of North America (RSNA) has held artificial intelligence competitions to tackle real-world medical imaging problems at least annually since 2017. This article examines the challenges and processes involved in organizing these...

[Medical image segmentation data augmentation method based on channel weight and data-efficient features].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
In computer-aided medical diagnosis, obtaining labeled medical image data is expensive, while there is a high demand for model interpretability. However, most deep learning models currently require a large amount of data and lack interpretability. To...