Computer Vision in Pulmonology

RSIP Vision’s image processing expertise in medical imaging is currently used in numerous projects, including many applications of computer vision in pulmonology. We are very proud of our contribution to lung medicine: feature detection, lung segmentation and countless other works in the pulmonary imaging field enabled our clients to give the means to physicians to save lives by giving faster and more appropriate treatment to all kind of lung diseases. You can read below about some of our breakthrough developments in Pulmonology and Bronchoscopy.
Chest Segmentation

Airways Segmentation

Image processing is a fundamental technique in the quest to identify lung cancer, one of the main causes of death among both men and women. Survival rate depends on the stage in which the disease is diagnosed and correct segmentation of airway vessels offers the most effective solution to determine the tumor's size and location, significantly improving diagnosis and treatment. Here is our recommended solution. Read more...

Lobes and Fissures Segmentation

Emphysema quantification and lung nodule detection are among the clinical applications which benefit the most from lobes segmentation in CT scans. Proper lung segmentation is key to determine the boundaries of lobes and prevent pleural damage during examination and treatment. When correctly located, diseases are treated faster and better, hence the call for RSIP Vision to find a faster alternative to time-consuming manual segmentation. Read More...

Lungs segmentation

RSIP Vision has built a lower respiratory tract segmentation software using advanced image processing algorithms. This region includes both lungs along with their pulmonary vasculature. This lung segmentation software takes advantage of the structure of vascular and capillary tree in the area as an exploratory tool for lungs segmentation, enabling both diagnosis and planning of invasive interventions. Read more...

Lungs tumors and nodules segmentation

It is visually more difficult to identify lung tumors than nodules, since the latter are supposed to have an elliptical shape, while the chromatic aspect of the former is quite hard to distinguish from healthy tissues on a CT image. We use graph cuts algorithms to overcome this difficulty in a way that is quick to perform, reliable and memory efficient. Our software of computer vision in pulmonology calculates the minimal energy in only a few seconds, to provide a quick and reliable 3D segmentation of lung tumors. Read more...

Lung vessel segmentation

Blood vessel segmentation of the lungs can help to identify important pulmonary diseases, characterizing nodules in the lungs, detecting pulmonary emboli and evaluating the lungs vasculature. Our technique of automatic pulmonary vessel segmentation completes very effectively the vessel tree structure provided by the CT scans of the lung, in such a way that the resulting image is more precise and matchlessly faster than any manual segmentation could be. Read More...

Lymph nodes detection

Analyzing pulmonary lymph nodes can give us valuable information for lung cancer diagnosis and treatment. This solution too uses advanced algorithm of computer vision for pulmonology; it also allows to overcome technical difficulties like low image contrast and high nodes variation, offering a drastic improvement over techniques currently used to detect lung lymph nodes. Read More...

Pulmonary embolism detection

Timely detection of pulmonary embolism via CT angiography is key to reduce mortality risks. Human detection of pulmonary embolism (being often too slow, RSIP Vision recommends a combination of bidimensional and tridimensional image-processing techniques to achieve computer-aided pulmonary embolism detection which enables prompter diagnosis and treatment. Read More...

Other Projects in Pulmonology

The work of RSIP Vision in Pulmonology and Bronchoscopy is not limited to the above subjects. We have successfully performed all kinds image processing projects of detection, segmentation, classification, registration and analysis of lung features and structure: emphysemas, cysts and more. Contact us and we will be happy to discuss your computer vision projects in Pulmonology. Read More...