The Temple University Hospital Digital Pathology Corpus
| Autor: | D. Houser, Y. Persidsky, N. Jhala, C. Campbell, Joseph Picone, Iyad Obeid, G. Shadhin, T. Farkas, R. Anstotz |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Computer science
business.industry Deep learning Interpretation (philosophy) Big data Digital pathology Clinical science University hospital Public domain Data science Field (computer science) 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine 030220 oncology & carcinogenesis Artificial intelligence business |
| Zdroj: | Signal Processing in Medicine and Biology ISBN: 9783030368432 |
| DOI: | 10.1109/spmb.2018.8615619 |
| Popis: | Digital pathology is a relatively new field that stands to gain from modern big data and machine learning techniques. In the United States alone, millions of pathology slides are created and interpreted by a human expert each year, suggesting that there is ample data available to support machine learning research. However, the relevant corpora that currently exist contain only hundreds of images, not enough to develop sophisticated deep learning models. This lack of publicly accessible data also hinders the advancement of clinical science. Our digital pathology corpus is an effort to place a large amount of clinical pathology images collected at Temple University Hospital into the public domain to support the development of automatic interpretation technology. The goal of this ambitious project is to create a corpus of 1M images. We have already released 10,000 images from 600 clinical cases. In this paper, we describe the corpus under development and discuss some of the underlying technology that was developed to support this project. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|