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.
On-the-Fly Improving Segment Anything for Medical Image Segmentation Using Auxiliary Online Learning
Abstract: The current variants of the Segment Anything Model (SAM), which include the original SAM and Medical SAM, still lack the capability to produce sufficiently accurate segmentation for medical ...
Abstract: Weakly-supervised learning methods have become increasingly attractive for medical image segmentation, but suffered from a high dependence on quantifying the pixel-wise affinities of ...
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