4 papers · 1 filter
SegMix:Shuffle-based Feedback Learning for Semantic Segmentation of Pathology Images
Zhiling Yan, Sicheng Chen, Tianyi Zhang +3
Segmentation is a critical task in computational pathology, as it identifies areas affected by disease or abnormal growth and is essential for diagnosis and treatment. However, acq…
SAMed-2: Selective Memory Enhanced Medical Segment Anything Model
Zhiling Yan, Sifan Song, Dingjie Song +11
Recent "segment anything" efforts show promise by learning from large-scale data, but adapting such models directly to medical images remains challenging due to the complexity of m…
Biomedical SAM 2: Segment Anything in Biomedical Images and Videos
Zhiling Yan, Weixiang Sun, Rong Zhou +8
Medical image segmentation and video object segmentation are essential for diagnosing and analyzing diseases by identifying and measuring biological structures. Recent advances in…
Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models
Yixin Liu, Kai Zhang, Yuan Li +9
Sora is a text-to-video generative AI model, released by OpenAI in February 2024. The model is trained to generate videos of realistic or imaginative scenes from text instructions…