Largest open-source database for bone marrow cell images developed
November 2021
Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany
Every day, cytologists around the world use optical microscopes to analyse and classify samples of bone marrow cells thousands of times. This method to diagnose blood diseases was established more than 150 years ago, but it suffers from being very complex. Here, the researchers developed the largest open-access database on microscopic images of bone marrow cells to date. The database consists of more than 170,000 single-cell images from over 900 patients with various blood diseases. On top of the database, the researchers have developed a neural network that outperforms previous machine learning algorithms for cell classification in terms of accuracy, but also in terms of generalizability. This study is a step toward automated evaluation of bone marrow cell morphology using state-of-the-art image-classification algorithms. The researchers aim to further expand their bone marrow cell database to capture a broader range of findings and to prospectively validate their model. The database and the model are freely available for research and training purposes – to educate professionals or as a reference for further AI-based approaches, e.g. in blood cancer diagnostics.
Highly accurate differentiation of bone marrow cell morphologies using deep neural networks on a large image data set
Carsten Marr
Added on: 05-12-2022
[1] https://ashpublications.org/blood/article/138/20/1917/477932/Highly-accurate-differentiation-of-bone-marrow[2] https://www.bionity.com/en/news/1173656/fighting-blood-diseases-with-artificial-intelligence.html
