ActiveFreq: Integrating Active Learning and Frequency Domain Analysis for Interactive Segmentation

ArXi:2603.11498v1 Announce Type: new Interactive segmentation is commonly used in medical image analysis to obtain precise, pixel-level labeling, typically involving iterative user input to correct mislabeled regions. However, existing approaches often fail to fully utilize user knowledge from interactive inputs and achieve comprehensive feature extraction. Specifically, these methods tend to treat all mislabeled regions equally, selecting them randomly for refinement without evaluating each region's potential impact on segmentation quality.