With New Omega Tool, Scientists can Rapidly Analyze Complex Biological Images through AI-Powered 'Conversations'

In a new research article, scientists at Chan Zuckerberg Biohub San Francisco (CZ Biohub SF) describe Omega, an open-source software tool that significantly advances the field of bioimage analysis. Omega harnesses the power of large language models (LLMs) to enable scientists to process and analyze biological images through natural language conversations rather than having to issue formal commands or write code.

Created by Loïc A. Royer and his team, and documented in a paper published June 10, 2024 in Nature Methods, Omega is a plug-in for napari, an open-source image viewer used worldwide in diverse scientific fields, especially in biomedical research.

Omega is tightly integrated with various LLMs, including OpenAI’s ChatGPT, allowing scientists to conduct sophisticated bioimage processing and analysis through intuitive, conversational interactions that issue all the required commands to the napari software in the background.

"Omega allows users to quickly generate and edit code to solve complex image processing tasks," explained Royer, a senior group leader and director of imaging AI at CZ Biohub SF. "You still need to understand the basics of image analysis, but Omega significantly speeds up the process."

By prioritizing ease of use, Omega democratizes bioimage analysis, as researchers without extensive programming skills can use Omega to perform high-level analyses, accelerating their workflow and generating greater insight into their imaging data. Furthermore, Omega’s collaborative features, such as a shared code editor, enhance teamwork and knowledge sharing within the scientific community, according to Royer.

Omega's features include:

  • Interactive image analysis: Users can instruct Omega to perform specific tasks, such as segmenting cell nuclei, counting objects, and generating detailed reports, all through simple conversational prompts.
  • On-demand widget creation: Omega can create custom widgets tailored to user-defined tasks, facilitating specialized image filtering, transformations, and visualizations.
  • An AI-augmented code editor: Omega includes an intelligent code editor that enhances code management with automatic commenting, error detection, and correction features.
  • Multimodal capabilities: Beyond text, Omega can interpret visual data, integrating multiple data types to provide comprehensive image analysis.

With the recent rise of LLMs and other AI platforms, Royer has envisioned a future in which bioimaging researchers will engage in dialogues with the software tools they depend on, rather than simply "issuing commands."

"The idea for Omega began with an invited perspective piece published in Nature Methods in 2023, in which I predicted that in the very near future bioimage analysis tasks will be solved through 'conversations with the machine,'" said Royer. "Omega is a significant stride toward this vision."

Members of the scientific community are already making use of Omega, which has been available for download from a GitHub repository since May 2023, with regular updates posted since then. "The feedback has been overwhelmingly positive - the software is being downloaded approximately 2,000 times per month - and it has inspired other researchers to explore similar ideas," said Royer.

The source code for Omega is openly available on GitHub, inviting contributions and collaboration from the global research community. This openness ensures that Omega will continually evolve, Royer said, incorporating the latest technological advancements to meet the ever-changing needs of scientists worldwide.

Looking ahead, Royer and his team plan to not only maintain Omega, but to continue enhancing its capabilities. "We plan to make Omega smarter and more robust, and compatible with the best and latest LLMs as they appear," he said.

Despite the striking recent advancements in LLMs, however, Royer emphasized that human expertise remains essential in research. "There will always be a need for human experts, but tools like Omega are going to remove bottlenecks, such as the need for coding skills to turn ideas into reality, and will dramatically increase productivity in science."

For more information about Omega, or to access the source code, please visit the GitHub repository.

Royer LA.
Omega - harnessing the power of large language models for bioimage analysis.
Nat Methods. 2024 Jun 10. doi: 10.1038/s41592-024-02310-w

Most Popular Now

AI also Assesses Dutch Mammograms Better…

AI is detecting tumors more often and earlier in the Dutch breast cancer screening program. Those tumors can then be treated at an earlier stage. This has been demonstrated by...

RSNA AI Challenge Models can Independent…

Algorithms submitted for an AI Challenge hosted by the Radiological Society of North America (RSNA) have shown excellent performance for detecting breast cancers on mammography images, increasing screening sensitivity while...

Unlocking the 10 Year Health Plan

The government's plan for the NHS is a huge document. Jane Stephenson, chief executive of SPARK TSL, argues the key to unlocking its digital ambitions is to consider what it...

AI can Find Cancer Pathologists Miss

Men assessed as healthy after a pathologist analyses their tissue sample may still have an early form of prostate cancer. Using AI, researchers at Uppsala University have been able to...

Alcidion Grows Top Talent in the UK, wit…

Alcidion has today announced the addition of three new appointments to their UK-based team, with one internal promotion and two external recruits. Dr Paul Deffley has been announced as the...

How AI could Speed the Development of RN…

Using artificial intelligence (AI), MIT researchers have come up with a new way to design nanoparticles that can more efficiently deliver RNA vaccines and other types of RNA therapies. After training...

AI, Full Automation could Expand Artific…

Automated insulin delivery (AID) systems such as the UVA Health-developed artificial pancreas could help more type 1 diabetes patients if the devices become fully automated, according to a new review...

MIT Researchers Use Generative AI to Des…

With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA). Using generative AI algorithms, the research...

Penn Developed AI Tools and Datasets Hel…

Doctors treating kidney disease have long depended on trial-and-error to find the best therapies for individual patients. Now, new artificial intelligence (AI) tools developed by researchers in the Perelman School...

AI Hybrid Strategy Improves Mammogram In…

A hybrid reading strategy for screening mammography, developed by Dutch researchers and deployed retrospectively to more than 40,000 exams, reduced radiologist workload by 38% without changing recall or cancer detection...

Routine AI Assistance may Lead to Loss o…

The introduction of artificial intelligence (AI) to assist colonoscopies is linked to a reduction in the ability of endoscopists (health professionals who perform colonoscopies) to detect precancerous growths (adenomas) in...

New Training Year Starts at Siemens Heal…

In September, 197 school graduates will start their vocational training or dual studies in Germany at Siemens Healthineers. 117 apprentices and 80 dual students will begin their careers at Siemens...