NucEval: A Robust Evaluation Framework for Nuclear Instance Segmentation
In computational pathology, nuclear instance segmentation is a fundamental task with many downstream clinical applications. With the advent of deep learning, many approaches, including convolutional neural networks (CNNs) and vision transformers (ViTs), have been proposed for this task, along with both machine learning-based and non-machine learning-based pre- and post-processing techniques to further boost performance. However, one fundamental aspect that has received less attention is the evaluation pipeline. In this study, we identify four key issues associated with nuclear instance segmentation evaluation and propose corresponding solutions. Our proposed modifications, namely handling...
| Authors | Amirreza Mahbod, Ramona Woitek, Jeanne Shen |
|---|---|
| Primary category | cs.CV |
| Published | 4 May 2026 |
| Last updated at source | 4 May 2026 |
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