Automated Classification of Cell Shapes: A Comparative Evaluation of Shape Descriptors

2024-11-01 · Valentina Vadori, Antonella Peruffo, Jean-Marie Graïc, Livio Finos, Enrico Grisan

This study addresses the challenge of classifying cell shapes from noisy contours, such as those obtained through cell instance segmentation of histological images. We assess the performance of various features for shape classification, including Elliptical Fourier Descriptors, curvature features, and lower dimensional representations. Using an annotated synthetic dataset of noisy contours, we identify the most suitable shape descriptors and apply them to a set of real images for qualitative analysis. Our aim is to provide a comprehensive evaluation of descriptors for classifying cell shapes, which can support cell type identification and tissue characterization-critical tasks in both biological research and histopathological assessments.

📄 PDF Abstract BibTeX arXiv:2411.00561

Code (1)

Vadori/CytoArk 공식 구현 tf

Tasks

Instance Segmentation Semantic Segmentation

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