Computer

Learning with limited target data to detect cells in cross-modality images
Deep neural networks have achieved excellent cell or nucleus quantification performance in microscopy images, but they often suffer …
Fuyong Xing, Xinyi Yang, Toby C. Cornish, Debashis Ghosh
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Bidirectional Mapping-Based Domain Adaptation for Nucleus Detection in Cross-Modality Microscopy Images
Cell or nucleus detection is a fundamental task in microscopy image analysis and has recently achieved state-of-the-art performance by …
Fuyong Xing, Toby C. Cornish, Tellen D. Bennett, Debashis Ghosh
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Artificial intelligence for automating the measurement of histologic image biomarkers
Artificial intelligence has been applied to histopathology for decades, but the recent increase in interest is attributable to …
Toby C. Cornish
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Artificial intelligence for automating the measurement of histologic image biomarkers
Generative Adversarial Domain Adaptation for Nucleus Quantification in Images of Tissue Immunohistochemically Stained for Ki-67.
PURPOSE: We focus on the problem of scarcity of annotated training data for nucleus recognition in Ki-67 immunohistochemistry …
Xuhong Zhang, Toby C. Cornish, Lin Yang, Tellen D. Bennett, Debashis Ghosh, Fuyong Xing
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Pixel-to-Pixel Learning With Weak Supervision for Single-Stage Nucleus Recognition in Ki67 Images
OBJECTIVE: Nucleus recognition is a critical yet challenging step in histopathology image analysis, for example, in Ki67 …
Fuyong Xing, Toby C. Cornish, Tell Bennett, Debashis Ghosh, Lin Yang
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