Developed for automatic segmentation of Nuclei in Brightfield images. Identification and segmentation of individual nuclei is of interest in many applications. Nuclei can be difficult to detect accurately and precisely across different images using traditional image analysis with feature engineering. This APP utilizes artificial intelligence (AI) for automatic nuclei detection in H&E and IHC stained tissue of various types including breast, prostate, liver, stomach and kidney. It consists of a pre-trained deep neural network and the APP is ready for use without additional training.
The APP function as a template where the user can easily configure it to fulfill their needs using the Visiopharm Author™ module. The APP currently has three configuration options which can be switched on and off as needed:
- Count of total number of nuclei for H&E and/or IHC images
- Classification of DAB positive and negative nuclei to compute the positive percentage for IHC images
- Classification of DAB positivity (negative, 1+, 2+, 3+) to compute the H-score for IHC images.
It is also possible for the user to customize the APP by adding other post-processing steps and/or output variables as needed.