Interpretative guides for interacting with tissue atlas and digital pathology data using the Minerva browser
Rashid, R.; Chen, Y.-A.; Hoffer, J.; Muhlich, J. L.; Lin, J.-R.; Krueger, R.; Pfister, H.; Mitchell, R.; Santagata, S.; Sorger, P.
Show abstract
The recent development of highly multiplexed tissue imaging promises to substantially accelerate research into basic biology and human disease. Concurrently, histopathology in a clinical setting is undergoing a rapid transition to digital methods. Online tissue atlases involving highly multiplexed images of research and clinical specimens will soon join genomics as a systematic source of information on the molecular basis of disease and therapeutic response. However, even with recent advances in machine learning, experience with anatomic pathology shows that there is no immediate substitute for expert visual review, annotation, and description of tissue images. In this perspective we review the ecosystem of software available for analysis of tissue images and identify a need for interactive guides or "digital docents" that allow experts to help make complex images intelligible. We illustrate this idea using Minerva software and discuss how interactive image guides are being integrated into multi-omic browsers for effective dissemination of atlas data.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning 94%
- The UCSC Xena platform for public and private cancer genomics data visualization and interpretation 92%
- Nanopore adaptive sequencing for mixed samples, whole exome capture and targeted panels. 92%
Similar papers in this journal
- ModularImageAnalysis (MIA): Assembly of modularised image and object analysis workflows in ImageJ 96%
- CellPhePy: a Python implementation of the CellPhe toolkit for automated cell phenotyping from microscopy time-lapse videos 95%
- Setting up an institutional OMERO environment for bioimage data: perspectives from both facility staff and users 95%
Similar papers in this journal
- AI for IACUC: Accurate Initial Assessment of Institutional Animal Care and Use Committee Protocols 90%
- Prime editing outperforms homology-directed repair as a tool for CRISPR-mediated variant knock-in in zebrafish 86%
- Refined Tamoxifen Administration in Mice by Encouraging Voluntary Consumption of Palatable Formulations. 85%
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.