AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Three Digital Imaging and Communications in Medicine (DICOM) formatted datasets are introduced, complementing NLST CT images, shared as analysis results in the National Cancer Institute Imaging Data Commons (IDC).
Development and evaluation of computational pathology methods require access to large and diverse datasets. Over the past decade, various initiatives invested significantly into collecting, centralizing, and sharing pathology imaging data. In contrast, sharing of image-derived data such as region-of-interest delineatio...
Abstract Background We sought to develop a deep learning (DL) model to enable fully automated 3D segmentation and volumetric assessment of meningioma burden with a specific emphasis on generalizing to high-grade and posttreatment meningiomas to improve interobserver variability and decrease reader time investment in tu...
The results show that DG methods, particularly those that explicitly regularize the learning process, improve out-of-domain generalization, but do not fully close the gap with in-domain performance, underscore the necessity of incorporating DG strategies to develop clinically deployable AI models.
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