Kobe, Japan

Krupali Jain



Average Co-Inventor Count = 6.2

ph-index = 2

Forward Citations = 8(Granted Patents)


Company Filing History:


Years Active: 2021-2023

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4 patents (USPTO):

Title: Krupali Jain: Innovator in Image Analysis Technology

Introduction

Krupali Jain is a notable inventor based in Kobe, Japan. He has made significant contributions to the field of image analysis, particularly in the context of deep learning algorithms. With a total of 4 patents to his name, Jain's work is at the forefront of technological advancements in medical imaging.

Latest Patents

Jain's latest patents include an image analysis method, apparatus, program, and learned deep learning algorithm. This invention provides a method for generating data that indicates a region of a cell nucleus in an image of a tissue or a cell. The method utilizes a deep learning algorithm of a neural network structure to analyze images, generating data that highlights the cell nucleus in the analysis target image. Another significant patent focuses on an image analysis method for determining the tumorigenic state of tissues or cells. This method also employs a deep learning algorithm to analyze images and generate data indicating the tumorigenic state of the analyzed tissues or cells.

Career Highlights

Throughout his career, Krupali Jain has worked with prominent organizations such as Sysmex Corporation and the National Cancer Center. His experience in these institutions has allowed him to develop and refine his innovative techniques in image analysis.

Collaborations

Jain has collaborated with several professionals in his field, including Yosuke Sekiguchi and Kazumi Hakamada. These collaborations have contributed to the advancement of his research and the successful development of his patented technologies.

Conclusion

Krupali Jain's contributions to image analysis technology through his innovative patents and collaborations highlight his role as a leading inventor in the field. His work continues to impact medical imaging and diagnostics significantly.

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