Lung carcinoma on an xray image of lungs.

Lung cancer, also known as lung carcinoma, is a malignant lung tumor characterized by uncontrolled cell growth in tissues of the lung. This growth can spread beyond the lung by the process of metastasis into nearby tissue or other parts of the body. Most cancers that start in the lung, known as primary lung cancers, are carcinomas. The two main types are small-cell lung carcinoma (SCLC) and non-small-cell lung carcinoma (NSCLC).

The most common symptoms are coughing (including coughing up blood), weight loss, shortness of breath, and chest pains.

The vast majority (85%) of cases of lung cancer are due to long-term tobacco smoking.

Smoking, a main cause of small cell and non-small cell lung cancer, contributes to 80 percent and 90 percent of lung cancer deaths in women and men, respectively. Men who smoke are 23 times more likely to develop lung cancer. Women are 13 times more likely, compared to never smokers. Source: lung.org

About 10–15% of cases occur in people who have never smoked. These cases are often caused by a combination of genetic factors and exposure to radon gas, asbestos, second-hand smoke, or other forms of air pollution. Lung cancer may be seen on chest radiographs and computed tomography (CT) scans.

Lung cancer is the most commonly occurring cancer in men and the third most commonly occurring cancer in women. There were 2 million new cases in 2018.

The Solution

The ANN developed by Skychain team member Ilya Kuznetsov, will save millions of lives as it can diagnose lung cancer at its early stages.

When developing the neural network our specialist used the dataset from a LUNA16 challenge, which consisted of 355 .mhd files, which are, in fact, 3D CAT scans of lungs.

The neural network is based on the U-net architecture, since it was most suitable for the task of image segmentation, however, it has 34 million parameters and did not allow to process 512x512 images,

therefore, in order to avoid loss of accuracy and acceleration of learning, a lot of parameters were optimized. As a result, the neural network had 3.5 million parameters.

It took us 2 months to create this ANN and the results were quite impressive.

Reached by our ANN for lung cancer detection.

Initially, the LUNA16 competition implied to simply determine the likelihood of cancer in the specific coordinates and indicate it with the coordinates and give the answer in a text file with numbers, but our ANN is able to do more — select the nodes with suspected cancer in the image, which is much more convenient and clearer compared to the numbers.

This neural network allows to immediately process the entire 3D image and mark all nodes suspicious for cancer.

How does it work? Take a look at these two animations: