Platform for Pathology Marking and Analysis, Applied to Medical Imaging

Nowadays, with the exploitation of artificial intelligence, the registration and identification of pathologies in medical images is required. In the present work we develop a platform for the tagging of pathologies found in medical images, the system is designed to provide physicians with an efficient and accurate tool for the diagnosis and monitoring of various diseases. Using Python as the main programming language, libraries such as SimpleITK for image analysis and Django for the creation of a user-friendly web interface will be used. The integration of LabelMe will allow users to mark regions of interest in medical images such as X-rays, mammograms, CT scans, MRI images among other imaging modalities, in the various image formats such as DICOM and NRRD formats. The system will allow the marking of images by medical specialists, as well as the analysis of the markings to locate areas where they coincide by more than two physicians. The platform is designed for the marking of multiple images in different formats and modalities.