Tokyo, Japan

Yoshinori Itai

This inventor holds 19 USPTO granted patents and 4 published patent applications and 4 EPO patents, primarily in Medical Image Processing. Top assignee: Fujifilm Corporation. Active years: 2015-2025.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Yoshinori Itai. Retrieved from https://idiyas.com/inventor/yoshinori-itai

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank
USPTO Granted Patents = 19 

% Patents Active = 84.2

 

Average Co-Inventor Count = 1.1

ph-index = 2

Forward Citations = 49(Granted Patents)


Location History:

  • Minato-ku, JP (2015)
  • Tokyo, JP (2015 - 2020)

Company Filing History:


Years Active: 2015-2025

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Areas of Expertise:
Image Analysis
Cartilage Quantification
Virtual Endoscopy
Image Display
Surgery Assistance
Medical Imaging
Image Processing
Mapping Image Generation
19 patents (USPTO):Explore Patents

Title: Innovations by Yoshinori Itai: Pioneering Advances in Image and Cartilage Analysis

Introduction

Yoshinori Itai, based in Tokyo, Japan, is a distinguished inventor known for his significant contributions to the fields of image analysis and medical technology. With a remarkable portfolio of 19 patents, Itai has consistently demonstrated his commitment to innovation. His work primarily focuses on enhancing the analysis of images and developing methodologies for quantifying cartilage, which are crucial for various applications in healthcare and beyond.

Latest Patents

Yoshinori Itai's recent patents reflect his pioneering spirit in advanced technology solutions. One notable invention is the "Image Analysis Device," which comprises an analysis unit that processes input image data using predefined analysis functions. This device incorporates a control unit that determines the appropriate analysis function to activate based on analysis results and preset conditions, thereby optimizing the process of image analysis.

Another breakthrough is the "Cartilage Quantification Device." This invention involves a sophisticated method that allows the extraction of bone and cartilage regions from a three-dimensional image. Itai's device features a projection direction determination unit that identifies the direction for projecting these regions and a projection image generation unit that creates a comprehensive projection image. Additionally, a quantification unit calculates the cartilage region's quantitative value based on this projection, providing valuable insights for medical applications.

Career Highlights

Yoshinori Itai is currently affiliated with Fujifilm Corporation, where he leverages his expertise in technology and innovation. His tenure at the company showcases his ability to integrate advanced research with practical applications, resulting in tools that enhance diagnostic capabilities in healthcare. His inventions are not just theoretical; they serve critical functions that aid medical professionals in their assessments and treatment plans.

Collaborations

Throughout his career, Itai has had the opportunity to collaborate with talented colleagues, including Jun Masumoto and Yuanzhong Li. These partnerships have fostered an environment of creativity and shared expertise, allowing for the advancement of innovative technologies that resonate within the industry.

Conclusion

Yoshinori Itai's work exemplifies the spirit of innovation, particularly in the realms of image analysis and medical technology. With a diverse array of patents, he has made substantial contributions to enhancing diagnostic tools and methodologies. As he continues to develop groundbreaking solutions at Fujifilm Corporation, the impact of his inventions will undoubtedly resonate in the fields of healthcare and beyond. The future is bright for both Itai and the numerous advancements he will bring forth in the years to come.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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