The present invention relates to lung measurement. In order to provide enhanced information about a patient that facilitates further assessment steps, 2D X-ray image data of a patients chest is provided, and the image data is segmented to identify lung structures to provide segmented image data separated from un-segmented areas. Further, spatial lung volume information is extracted from the image data using the segmented image data derived from the image data. Still further, lungs symmetry information is determined using the extracted spatial lung volume information. Finally, the lungs symmetry information is provided to a user. For example, a 2D X-ray image data of a patients chest is provided (84) and a lungs mask image is formed (86) after the step of segmenting the input image data. Then, the lungs mask image is used to define areas, within which a predetermined adaptation is applied (88) to the original 2D X-ray image data producing a thorax mask image. Next, left and right images are provided (90) showing the left and the right spatial lungs volume information of the regions defined originally by the lungs mask image. Finally, based on the spatial lungs volume information, lungs symmetry information or total lung volumes may be calculated and provided (92).
