Chest X-Ray Anomalous Object Detection and Classification Framework for Medical Diagnosis

The development of explanatory intelligence in connection to intelligent diagnostic systems is critical in medical science. The paper provides ways for application of methods and models of artificial intelligence in diagnostics of common thoracic lung diseases built on the data of multimodal radiation diagnostics from chest x-ray (CXR) dataset. The proposed framework for object detection and classification is based on deep machine learning approaches empowered with fuzzy. The artificial intelligence and direction of its use from the point of view of data processing, object detection and classification are discussed. We discuss the stages of intelligent processing of diagnostic data. The preliminary processing of images, segmentation of images to highlight the investigated diagnostic objects and the classification of these objects to determine, whether they are malignant or benign.