Fumiya Inaba MSc Candidate

I am an MSc student in the Interdisciplinary Oncology Program at the BC Cancer Research Centre, under the guidance of Dr. Martial Guillaud and Dr. Calum MacAulay. My research interests lie in the field of digital pathology with a special emphasis: leveraging state-of-the-art algorithms, such as machine/deep learning, for medical image analysis. I obtained my Bachelor's degree in Medical Laboratory Sciences at the University of British Columbia, where I developed a keen interest in the applications of machine learning and data science in the pathology field, ultimately leading me to my current position. 

My current research aims to advance the understanding of cancer progression and its underlying biology through computational methods. Advanced algorithms, such as instance-segmentation of nuclei in whole slide images, enable a detailed analysis not only at the level of individual cells but also of their interactions and architectural distribution in tissue sections. Ultimately, my goal is to contribute to the development of a 3D simulation model that illustrates how cancer may progress within tissues or organs, depending on specified parameters.

The increasing availability and digitization of medical data have enormous transformative potential in the advancement of digital pathology research. However, to fully realize this potential, there must be a structured framework to manage the vast amount of data effectively. Through DASH, I aspire to contribute not only to the development of such frameworks but also to projects that will make data and its analyses more robust, scalable, and reproducible.

Research Interests: Digital pathology, Image processing, Machine learning, Deep Learning, Statistical analysis, Histopathology, Oncology, Spatial biology