Feature extraction from super-resolution ultrasound prostate cancer maps

Super-resolution ultrasound image analysis generates microscopic detail maps of entire organs by tracking individual microbubbles that are available in the blood stream. This is achieved by deploying sophisticated image analysis using statistical models. The resulting vascular architecture maps provide unprecedented detail that is unique to each patient, similar to a fingerprint. Additional information on blood flow dynamics creates a wealth of information that is difficult to process by trained human observers. State-of-the-art pattern recognitions will be deployed as well as artificial intelligence in order to recognise image feature that are specific to the detection of tumour patterns. These computationally intensive methods will be achieved using biological models and existing patient data. The output of this project will provide a decision making tool for clinicians, as it is recognised that operator subjectivity remains one of the biggest hurdles in standardising medical imaging diagnosis. 

Collaborators: Prof Hashim Ahmed, Dr Taimur Shah (Imperial College London hospitals)

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