| rBPS {SAFARI} | R Documentation |
Reconstructed Binary Pathology Slide
Description
This reconstructed binary image was first represented as a three-class image, prepared using a tumor recognition system (ConvPath) developed by the Quantitative Biomedical Research Center. The original whole-slide image comes from a lung cancer patient in the Lung Screening Study (LSS) subcomponent of NLST. Specifically, this is an image from an H&E-stained slide that was obtained as part of a pathology specimen collection.
Usage
data(rBPS)
Format
rBPS is a 314-by-224 binary matrix where each entry
corresponds to a tissue or region in the H&E image. In our case the ones and
zeros indicate an empty region or tumor tissue, respectively.
Source
Original H&E slide available at https://biometry.nci.nih.gov/cdas/nlst/.
References
ConvPath: A software tool for lung adenocarcinoma digital pathological image analysis aided by a convolutional neural network. (2019) EBioMedicine.