2 citations · 4 across the 6 of their papers we have counts for
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cs.CV2023★ 2 cited
All-in-SAM: from Weak Annotation to Pixel-wise Nuclei Segmentation with Prompt-based Finetuning
Can Cui, Ruining Deng, Quan Liu +5
The Segment Anything Model (SAM) is a recently proposed prompt-based segmentation model in a generic zero-shot segmentation approach. With the zero-shot segmentation capacity, SAM…
eess.IV2023
Cross-scale Multi-instance Learning for Pathological Image Diagnosis
Ruining Deng, Can Cui, Lucas W. Remedios +12
Analyzing high resolution whole slide images (WSIs) with regard to information across multiple scales poses a significant challenge in digital pathology. Multi-instance learning (M…