Publications by authors named "Dotun Oyekunle"
Article Synopsis
- * A 2D convolutional neural network (CNN) was trained on synthesized data and tested on various datasets, achieving notable precision (85%) and recall (80%) in identifying motion issues.
- * The model demonstrated excellent agreement with a radiologist's assessments (93%) and correlates strongly with an image quality metric, aiming to streamline the quality assessment process, especially in low-resource environments.
Article Synopsis
- Machine learning can work well, but it often struggles to make accurate predictions on new data, which is called out-of-sample generalizability.
- To solve this problem, researchers are using a method called Federated ML that allows computers to share information about how well they're learning without actually sharing the data itself.
- In a big study with 71 locations around the world, scientists created a model to help detect brain tumors more accurately, showing a significant improvement compared to older methods and hoping to help with rare illnesses and data sharing in healthcare.
Low-field MR scanners are more accessible in resource-constrained settings where skilled personnel are scarce. Images acquired in such scenarios are prone to artifacts such as wrap-around and Gibbs ringing. Such artifacts negatively affect the diagnostic quality and may be confused with pathology or reduce the region of interest visibility.
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