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cs.CV2023
Evaluation and improvement of Segment Anything Model for interactive histopathology image segmentation
SeungKyu Kim, Hyun-Jic Oh, Seonghui Min +1
With the emergence of the Segment Anything Model (SAM) as a foundational model for image segmentation, its application has been extensively studied across various domains, includin…
cs.CV2023
Scribble-supervised Cell Segmentation Using Multiscale Contrastive Regularization
Hyun-Jic Oh, Kanggeun Lee, Won-Ki Jeong
Current state-of-the-art supervised deep learning-based segmentation approaches have demonstrated superior performance in medical image segmentation tasks. However, such supervised…
cs.CV2023
DiffMix: Diffusion Model-based Data Synthesis for Nuclei Segmentation and Classification in Imbalanced Pathology Image Datasets
Hyun-Jic Oh, Won-Ki Jeong
Nuclei segmentation and classification is a significant process in pathology image analysis. Deep learning-based approaches have greatly contributed to the higher accuracy of this…