Deep learning - An efficient method for medical image analysis
N. Lavanya Devi, C. N. Savithiri, P. Thirumurugan, P. Shanthakumar · AIP conference proceedings · 2022
Medical imaging provides the visual representation of internal organs of the body which facilitate in diagnosis, monitoring health etc. Previously, the automated diagnosis procedure was done using edge detection and tedious mathematical computations. With the advancement in artificial intelligence, medical imaging is now supporting the diagnosis of cancer, diabetic retinopathy, Detection of Alzheimer’s and Parkinson’s disease, brain injury etc. Diagnosis through medical imaging has reduced the mortality rate drastically especially in the field of cancer. In order to decrease the probability of human error machine learning came into existence. The commonly used machine learning algorithms are K-Nearest Neighbors, Supported Vector Machine (SVM), and Decision Trees etc. But machine learning method has its own limitation of high dependency to the features extracted which depends on many factors. In order to improve the efficiency by removing the dependency on feature deep learning method came into existence. This paper has made a detailed survey on the application of deep learning method in health care service.