Guiding the Guidance: A Comparative Analysis of User Guidance Signals for Interactive Segmentation of Volumetric Images
Zdravko Marinov, Rainer Stiefelhagen, Jens Kleesiek

TL;DR
This paper compares different user guidance signals for interactive volumetric image segmentation, introduces an adaptive heatmap guidance method, and demonstrates significant performance improvements on medical datasets, advancing clinical applicability.
Contribution
It provides a comprehensive analysis of guidance signals, proposes an adaptive heatmap approach, and shows improved segmentation accuracy in medical imaging tasks.
Findings
Adaptive heatmaps improve segmentation accuracy by 14% Dice.
Choosing the right guidance signal is crucial for interactive segmentation.
The method enhances clinical workflow readiness for medical image segmentation.
Abstract
Interactive segmentation reduces the annotation time of medical images and allows annotators to iteratively refine labels with corrective interactions, such as clicks. While existing interactive models transform clicks into user guidance signals, which are combined with images to form (image, guidance) pairs, the question of how to best represent the guidance has not been fully explored. To address this, we conduct a comparative study of existing guidance signals by training interactive models with different signals and parameter settings to identify crucial parameters for the model's design. Based on our findings, we design a guidance signal that retains the benefits of other signals while addressing their limitations. We propose an adaptive Gaussian heatmaps guidance signal that utilizes the geodesic distance transform to dynamically adapt the radius of each heatmap when encoding…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAI in cancer detection · Artificial Intelligence in Healthcare and Education · COVID-19 diagnosis using AI
MethodsHeatmap
