Olympus and the Jikei University School of Medicine Develop an Artificial Intelligence (AI) System to Precisely Calculate Sperm Motility in Real Time Collaborative research will help embryologists accurately and quickly identify good sperm

November 11, 2019


Example calculation of sperm motility (green: fast, red: slow)

Good sperm (yellow-green) move fast and in a straight line.
In contrast, low-quality sperm (brown) move slowly and in a zigzag path.
By calculating sperm motility in real time, our AI system can help embryologists quickly identify good sperm in the ICSI workflow.


Olympus Corporation (President: Yasuo Takeuchi) announce the Olympus Corporation and the Jikei University School of Medicine made a breakthrough in their joint research1 by developing an AI-assisted sperm selection system that can calculate sperm motility in real time with high accuracy. The research aims to reduce the intracytoplasmic sperm injection (ICSI) workload and standardize the sperm selection process among embryologists2 as the demand for assisted reproductive technology grows.

After evaluating 1,066 sperm images in the research, the AI system learned the criteria to recognize sperm in a live image with high accuracy (99% sensitivity3 , 92% positive predictive value4 92%) and calculate its motility. This innovative AI technology can help embryologists distinguish fast-moving sperm from slow-moving sperm in real time. Going forward, the research team will develop the AI system to evaluate sperm morphology, including the sperm head and neck. The goals are to further enhance the AI and deploy a microscope equipped with this technology by December 2020.

Olympus, the department of obstetrics and gynecology at the Jikei University of Medicine, and LPIXEL Co., Ltd.5 will continue to collaborate to meet these goals as part of Olympus’ Office of Innovation6. The AI-powered microscope under development will help to solve challenges in the assisted reproductive technology workflow like the growing workload and lack of standardized selection criteria. This content was presented by the Jikei University School of Medicine in a paper called, "Study of the Feasibility of Supporting Favorable Sperm Selection by Machine Learning in Microinsemination" at the 64th Annual Meeting of the Japan Society of Reproductive Medicine on November 7 and 8, 2019.

1 News release on March 8, 2019: http://www.lederp.com/news/2019/nr01168.html

2 A medical technologist who operates assisted reproductive technology, such as ICSI and in vitro fertilization, under the guidance of physicians.

3 The rate at which the AI can detect sperm.

4 The percent of real the AI was able to correctly identify.

5 venture company originating at the University of Tokyo with image analysis expertise. The company’s goal is to strengthen the AI technology development of Olympus products.

6 Collaboration with companies and academic organizations with advanced technologies under our X (cross) Innovation program.

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