The article describes the development of the software module, which allows determining the size and volume of pulmonary nodules detected during low-dose computed tomography of the chest organs. The main focus of the article is on automatic quantification of nodules in accordance with the guidelines for the management of pulmonary nodules of the British Thoracic Society, the Fleischner Society, the Lung-RADS and European position statement on lung cancer screening. The approach presented is based on classical image processing methods and methods based on the use of neural networks (U-Net architecture). The input data are masks being obtained as a result of segmentation (it can be performed by a radiologist manually, in automatic or semi-automatic mode) of low-dose CT scans. The output data are DICOM image files being obtained from the original low-dose CT slice files by overlaying metadata, pulmonary nodule contours, long and short axes, and their lengths in mm, and a structured report (DICOM SR) containing lung nodule data in an easy-to-read format. An algorithm for calculating the position of the nodules relative to the lungs is also implemented for the possibility of comparing two studies of one patient in order to estimate the volume doubling time of the pulmonary nodules. The module being described is the part of the medical decision support system, that is being developed to solve the problems of reducing the heavy workload of radiologists and improve the accuracy of diagnosis of various diseases through the analysis of medical images.