Publications by authors named "Feiqiao Wang"
Article Synopsis
- Population-based cancer registries in the U.S. gather comprehensive data on cancer cases, including patient demographics, tumor details, treatments, and outcomes, to support cancer statistics and research.* -
- The project aims to enhance the NCI's SEER registry by integrating high-quality biospecimen data through digital pathology and advanced imaging techniques, promoting more consistent and objective analysis of cancer data.* -
- A curated repository of digitized pathology images has been established, alongside the development of automated tools for creating population cohorts and visualizing key features, ultimately improving the retrieval and analysis of cancer specimens.*
Well-curated sets of pathology image features will be critical to clinical studies that aim to evaluate and predict treatment responses. Researchers require information synthesized across multiple biological scales, from the patient to the molecular scale, to more effectively study cancer. This article describes a suite of services and web applications that allow users to select regions of interest in whole slide tissue images, run a segmentation pipeline on the selected regions to extract nuclei and compute shape, size, intensity, and texture features, store and index images and analysis results, and visualize and explore images and computed features.
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