ResourceLife Sciences
Robust identification of islets with variable morphology in H&E-stained pancreatic tissue using HALO AITM
22 Sept 2019In this application note, Indica Labs trains the HALO AITM VGG convolutional neural network (VGG-CNN) to identify islets within pancreatic tissue sections following H&E staining. It demonstrates how it is possible to build a robust classifier to accurately segment islets from surrounding exocrine tissue, irrespective of stain or morphological variability. This study highlights the potential for HALO AI to simplify the pathological evaluation of pancreatic tissue in metabolic research and toxicological pathology.
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Indica LabsHALO provides easy-to-use, spatially-resolved cell and area-based image analysis for digital pathology and whole tissue images.
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