Assistant Professor, Department of CT-UG, Kongu Engineering College
B.Sc.(IS), Department of CT-UG, Kongu Engineering College
Digital imaging systems are currently being used in medical diagnosis and research. Digital images refer to the collection of pixels or picture elements that vary in terms of brightness and color. Medical images, specifically refers to the images generated from modalities like CT (Computerized Tomography), Ultrasound and MRI (Magnetic Res- onance Imaging). The main notion behind the study of medical images is to equip the quality of imaging. The recent innovations greatly dealt with recognition of images through Deep Learning methodologies which is the subset of Machine Learning. It learns automatically from the machine by practice without the need of programming explicitly. The medicinal imaging system includes five major processing steps such as acquisition, augmentation, segmentation, feature extrac- tion/retrieval and categorization. Through deep learning process, pre- diction can be done easily for analysis purpose. In this paper, the tech- nologically advanced methods that are being currently in use in medical imaging and the different phases of analysis process, structural design of deep learning, along with the challenges are discussed.