Deep learning techniques for biomedical imaging

Abstract

In this chapter, we have discussed the physics of the common medical imaging techniques that are applied in the electromagnetic spectrum: electrical impedance tomography (EIT), magnetic resonance imaging (MRI), microwave imaging (MWI), and computed tomography (CT) scan. The EIT and MWI imaging techniques based on the electromagnetic theory and Maxwell's equations are specifically investigated with detail physics and imaging algorithms (BIM and DBIM) flowcharts. Then we explained the basic theories and structures of the machine learning and deep learning methods, and discussed their applications in medical imaging within the last decade. Particularly, we discussed the most recent deep learning network applications in medical imaging diagnosis, segmentation, and reconstruction. Furthermore, more advanced applications that combine the electromagnetic physics-based imaging methods with deep learning networks for imaging improvements are discussed in details through four recent EIT and MWI imaging studies published.