Imaris
World’s leading Interactive Microscopy Image Analysis software for 3D and 4D imaging.
Paid
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3D/4D Image Visualization
Image Segmentation
Object Tracking
StarDist
4.7
Free Users praise StarDist for its accuracy, ease of use, and versatility in segmenting star-convex objects in 2D and 3D images, though some note the need for strong GPU support for optimal performance.
Star-convex object detection for 2D and 3D images.
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Refined 3/4/2026
About StarDist
StarDist is a Python-based tool for object detection, particularly focused on segmenting objects with star-convex shapes in 2D and 3D images. It utilizes a deep learning model trained to predict distances from each pixel to the object boundary along a fixed set of rays, as well as object probabilities. The core architecture involves training a convolutional neural network on pairs of raw images and corresponding labeled images, where each pixel is assigned a unique object ID. The final segmentation is achieved through non-maximum suppression (NMS) of candidate polygons/polyhedra generated from the model's predictions. Key use cases include cell nuclei segmentation in microscopy images, histopathology image analysis, and general object detection in biological imaging applications. The tool is designed for researchers and practitioners in the fields of biology, medicine, and computer vision.
Core Capabilities
StarDist is a Python-based tool for object detection, particularly focused on segmenting objects with star-convex shapes in 2D and 3D images.
Main Tasks
Image Segmentation
Explore all tools that specialize in image segmentation. This domain focus ensures StarDist delivers optimized results for this specific requirement.
