Introduction ==================== Idiopathic Pulmonary Fibrosis (IPF) presents a prognosis of deterioration of pulmonary function responsible for 50% of cases referred for lung transplantation. IPF is frequently associated with a histological and radiological pattern of Usual Interstitial Pneumonia (UIP), and this radiological pattern is characterized in high resolution computed tomography (HRCT). Considering the complexity of the diagnostic decision making and the difficulties in performing a more objective evaluation of the pulmonary parenchyma, this poster presents the initial results of the computational algorithm, written in Python. The aim of the study is to automatically segment the lung area as a first step in the tool for quantitative and objective analysis of interstitial fibrosis pneumonia with Python algorithms. Material & Methods ==================== The algorithm proposed in this study, performs preprocessing through filters. Scikit-Image filters were used to perform the detection of CT edges. We used a public image database containing examinations in DICOM (Digital Imaging and Communications in Medicine) format of patients with interstitial lung diseases. The images are preprocessed using a library called Pydicom. Lung area segmentation was processed based on a region-targeting approach. The first step was to find through the algorithm of the Sobel filter the magnification map of the pixels in each tomographic cut. The second step consisted in performing a study of the histogram of each tomographic cut and then establishing mean border transition values ​​so that we could construct markers of these images. Finally, we use the Watershed Transform to fill the regions of the elevation map from the markers determined above. The Watershed method finded basins in image flooded from given markers, this method is also implemented by Scikit-Image. Conclusion ==================== The segmentation obtained allows the evaluation of the pulmonary parenchyma and can be applied to HRCT images of patients with interstitial fibrosis pneumonia, including suspected UIP, in order to obtain the image area (lung) where the classification analyzes will be performed of pulmonary opacities.