Threshold-based segmentation by selecting a target color vector in one of six color spaces (RGB, HSV, CIELAB, CIEXYZ, YCbCr or YIQ (NTSC)) and isolating pixels within a user-specified tolerance.
OpenWorldSAM pushes the boundaries of SAM2 by enabling open-vocabulary segmentation with flexible language prompts. [2026-1-4]: Demo release: we’ve added simple demos to run OpenWorldSAM on images ...
Abstract: Brain tumor segmentation plays a critical role in accurate diagnosis and treatment planning but remains challenging due to complex tumor boundaries and variations across MRI sequences.
Abstract: The U-Net algorithm, with its unique network structure and excellent performance, has become a classic algorithm in the field of image semantic segmentation. However, there are still some ...
Background: Accurate localization and segmentation of polyp lesions in colonoscopic images are crucial for the early diagnosis of colorectal cancer and treatment planning. However, endoscopic imaging ...
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