Development of AI Based Framework for The Classification Of Microscopic Images

Abstract

Microscopic image processing is a process of applying operations on an image newlinethat has been captured through a microscope. Recent advancement in imaging newlinetechnologies have simplified the acquisition of microscopic image data. Due to a newlinerapid growth of computer aided technologies, microscopic image processing has newlinegained tremendous popularity in various applications specially in medical sector. In newlinemedical science microscopic imaging analysis is used for the study of cell and tissue newlinestructure to perform various operations like classification, segmentation and newlinedetection to identify pattern of diseases at early stage. Many recent advancements newlinehave occurred in this domain to provide automated solutions to medical experts for newlinethe diagnostic procedure. newlineMicroscopic image classification is a critical task in various scientific and newlinemedical fields, which allows the researcher to analyse the complex structure and newlinepattern of microscopic images at different level in different domains. In this thesis, newlinework proposes the development of artificial-intelligence based framework for the newlineautomated classification of microscopic images. The proposed frameworks utilizing newlinethe advanced machine learning and deep learning methods to analyse and categorize newlinemicroscopic images based on their content and features. The proposed method newlineincludes data pre-processing, feature extraction, model training, and evaluation of the newlineclassification performance. Also, different deep learning-based models have been newlinedesigned for the analysis of microscopic images. The end-to-end development of newlinedeep learning-based models lead up to providing automation for microscopic data newlineanalysis and predictive decision making with enhanced efficiency of the system newlineacross various domains. newlineThe main motive of the presented work is to explore the efficacy of the newlinedifferent deep learning architecture, such as convolutional neural network (CNNs) newlineand transformer-based models, for microscopic image classification task so that the newlineautomated solutions can be provide