Taipei, Taiwan

Chin-Han Tsai

USPTO Granted Patents = 5 

 

Average Co-Inventor Count = 2.6

ph-index = 2

Forward Citations = 15(Granted Patents)


Company Filing History:


Years Active: 2014-2024

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5 patents (USPTO):Explore Patents

Title: Innovations by Chin-Han Tsai

Introduction

Chin-Han Tsai is a prominent inventor based in Taipei, Taiwan. He has made significant contributions to the field of medical imaging, particularly in the detection of diabetic retinopathy using advanced machine learning techniques. With a total of 5 patents to his name, Tsai's work exemplifies the intersection of technology and healthcare.

Latest Patents

One of Tsai's latest patents focuses on diabetic retinopathy detection using machine learning. This patent describes methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for computer-aided diagnosis of medical images. The process involves utilizing a machine learning model to analyze medical images, generating feature representations that aid in diagnosis. Another notable patent is an image pre-processing method and apparatus for fundoscopic images. This innovation involves obtaining a region of interest from a fundoscopic image, performing a smoothing process, and enhancing pixel value differences to improve image quality.

Career Highlights

Throughout his career, Chin-Han Tsai has worked with notable companies such as Giga-byte Technology Co., Ltd. and Acer Medical Inc. His experience in these organizations has allowed him to develop and refine his innovative ideas in medical imaging technology.

Collaborations

Tsai has collaborated with several professionals in his field, including Ming-Ke Chen and Tung-Ke Lu. These partnerships have contributed to the advancement of his research and the successful development of his patented technologies.

Conclusion

Chin-Han Tsai's contributions to medical imaging and machine learning demonstrate his commitment to innovation in healthcare. His patents reflect a deep understanding of technology's potential to improve diagnostic processes, ultimately benefiting patients and healthcare providers alike.

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