An Analysis of Pattern Recognition and Machine Learning Approaches on Medical Images
S. Jaya, M. Sneha Latha · Advances in computational intelligence and robotics book series · 2020
This chapter focuses on detailed overview of medical images as well as microscopic images to diagnosis the disease based on pattern recognition model in digital image processing. Pattern recognition is leading role in machine learning model which is used to detect the object such as text or character recognition, fingerprint recognition, face recognition, and biometric recognition. This chapter used pap smear images of cervical cancer to diagnosis a tissues by applying various image processing techniques followed by four tasks which are image acquisition, preprocessing, feature extraction, and object recognition. Cervical cancer is one of the very dangerous kind of cancer which may occur on the cervix part of the women. Diagnosis of tissue cells is based on the pixel variations of the images that may predict the cell is normal or abnormal state. This chapter presents machine learning algorithm of principle component analysis (PCA), Singular value decomposition (SVD), and linear discriminant analysis (LDA) under dimensionality reduction to recognize the pattern of the pap smear microscopic images.