Özet:

An important application of Dicom files is to use the image processing techniques in order to identify different organs or parts of organs, through segmentation. There are a lot of methods and algorithms employed in medical images semiautomatic segmentation and also many programs dedicated to specific functions and organs. The aim is to find new algorithms in order to have automatic segmentation capabilities for every organ and to compare the result to a database which can alert the doctor about a certain pathology which can be overlooked. The main objective of our research is to use segmentation algorithms for MRI (CT) Dicom files to identify different organs and to determine their properties, like dimensions, area, volume etc in order to produce a database containing these organs’ properties together with data regarding the anonymised patient, like age, weight, height, sex, race, residence etc. There were used: sets of Dicom anonymised files from MRI (CT) laboratories from two different regions in Romania and dedicated software developed based on an own algorithm for lungs segmentation, which also determines the lung volume. There was developed a dedicated software application based on an own algorithm for the lungs segmentation. The algorithm was previously validated through MatLab simulation. Based on the elements identified by this software there were obtained the data regarding patients and the values representing the lungs’ dimensions. All these represent the primary data for our database.

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