A Novel approach for Renal Cell Carcinoma Classification Using Vascular, Morphological and Spatial Information

Kidney cancer is one of the most common malignancies worldwide. The number of patients with kidney cancer is increasing every year due to aging of the population, obesity, diet, and lifestyle. The death rate due to kidney cancer is also increasing despite the introduction of new and advanced detection devices; also these methods are expensive, time consuming, subjective and might result in under/over treatment. We plan to develop cheap, fast and reliable methods to classify normal vs. kidney cancer and cancer sub-types. Our method makes the classification decision based on information from tissue structure and comparison with normal tissue. Success with this work will significantly improve assessing kidney tissue and provide clinically important information about the kidney tissue structure. Moreover, we envision that this method can be generalized to detection of another cancer types.

Faculty Supervisor:

Calum MacAulay

Student:

Partner:

Inria Sophia Antipolis - Méditerranée Research Centre

Discipline:

Engineering

Sector:

Education

University:

The University of British Columbia

Program: