Computer based histopathological image analysis for cancer grading and progression assessment
Supervisor: Dr Qianni Zhang
Research group(s): Multimedia and Vision
The assessment of pathological cancer regression after preoperative chemotherapy is mostly based on the assessment of tumour morphological features, such as the proportion of cancer cells in relation to the total tumour region, as well as biologically relevant histology features, such the tumour invasion front. Currently, this histopathological evaluation is performed by expert pathologists through visual assessment of the tumour microscopic slides. This is often time-consuming, expensive and may be unacceptably inconsistent and imprecise. This project aims at developing an intelligent system that enables automatic, precise, objective and reproducible assessment of tumour regression and precise characterisation of the tumour invasion front based on the digital scans of resected tumour tissue slides, by integrating beyond the state-of-the-art, specifically designed computer vision, image processing and machine learning schemes.