Using AI to Detect Lung Cancer from CT Scans




Medical scientists have beamed that to detect, diagnose, and treat a patient with cancer successfully, access to the right tools is essential. For instance, in England, lung cancer which happens to be one of the significance causes of death with an annual 1.6 million deaths attributed to it, is most times detected at a late stage living majority of these patients untreatable.
To diagnose lung cancer, physicians depend on the segmentation of lesions on the lungs by making use of a combination of PET and CT scans.  These are primarily used to determine the functional attributes of a lesion in addition to its anatomical characteristics and structure.
Poland-based Future Processing which happens to be one of the numerous members of NVIDIA’s inception program is working really hard to ensure it simplifies the use of these tools, thereby making the diagnosis process more economical, accurate, reliable, and accessible.
Furthermore, its medical imaging solutions business sector has collaborated with the medical imaging experts, research institutes and clinics all over the world to design and develop software that will enhance and adequately analyze images.
Dynamic contrast enhanced imaging, and the analysis of computed technology (CT), happens to be their significant areas of concentrations. The company’s research in this area is likely to lead to the increased utilization of CT scans in the discovery and examining of lung cancer.

A Picture Expresses A Thousand Words

Future Processing is working so hard to determine the best solution to the get rid of the need for the unification of PET and CT scans. This will enable doctors to make diagnosis and analysis based on CT scans.
By making use of the convolutional neural networks, they have been able to demonstrate that diagnoses from CT scans alone can be made efficient and accurate.
According to Dr. Jakub Nalepa, a senior research scientist at Future Processing, “Before the segmentation of active lesions there is the need for the co-registration of PET and CT sequences within a time-absorbing procedure.” He further stated that they are have been able to present a research analysis using CT scans, where they were able to demonstrate segmentation of a single image within a couple of minutes.
NVIDIA Tesla GPU accelerators are responsible for powering the acceleration in speed segments and is capable of making a tremendous difference for both doctors and patients. Furthermore, radiologists can save a tremendous amount of time and measure lesion progress by automatically segmenting the lesions.
It would be a huge relief for medical sites as they will be able to take care of their patients directly using only CT scanners and without the interception of PET scanners. This is pretty more economical for medical personals, as a CT scan costs between the sums of $1,200 to $3,200, while a PET scan which costs $3,000 to $6,000. Asides that, it also offers a better experience for patients, who will only undergo one scan.

Nalepa and his team of researchers have proven their approach to be responsible for the reduction of false positives, from 90.14 percent to 6.6 percent. They hope to develop a lasting solution to the lung cancer in the nearest future.