The Cancer Recognizer

Today cancer is one of the most widespread diseases on the Earth. Fortunately, it is possible to fight back with cancer if it is detected in time. Usually, it is done by taking a testing sample and sending it to the laboratory, where the example is put under the microscope. After enlarging by 400 or 1000 times, this sample is going to be inspected by the experienced doctor, who concludes whether this example includes cancer cells or not. Our development team has come up with an idea to mimic the detection process and to train AI-based system to recognize potentially dangerous cells. In order to achieve our goal, we are going to create a special system, based on CNN (convolution neural network), whose purpose is to analyze images from the dataset and make conclusions.

Before providing images to the system, we are going to “cut” every cell from the initial image (no matter if it has cancer or not) and thus create a new dataset that includes only cells. This procedure is using a few instruments from the OpenCV library. This technique is going to ease our system’s training process significantly.

The conclusion of the system is a prediction provided to the user about the current sample if it includes cancer cells and their amount is enough for diagnosing the cancer or not.

So far, the system is ready to diagnose only one type of cancer: mast cell. In the future, we are expecting to expand the system’s possibilities on other types of cancer.