Development of a deep learning approach for transferring gray-scale images acquired from photoacoustic imaging to histological-stained images
Project Description

Histological images are the gold standard in hospitals. Pathologists are used to histological images to make a judgment. To enhance the ease of use of novel microscopic imaging technique (e.g., photoacoustic microscopy) for pathologists to understand, it is crucial to transfer the images, which are normally in gray-scale, to histological-stained images. This project aims to develop a deep learning approach for transferring gray-scale images to histological-stained images

Supervisor
WONG Tsz Wai
Quota
1
Course type
UROP1000
UROP1100
Applicant's Roles

Applicant should be able to develop a convolution neural network or other networks that can reach the goal

Applicant's Learning Objectives

Through this project, the applicant will learn how to develop a convolution neural network for style transfer

Complexity of the project
Challenging