outputs/Background and Literature survey of Medical Image Analysis Im going to use CNN and RNN as models/research-5592575591713378695.txt

[{"title": "Machine Learning for Medical Image Analysis: A Survey", "href": "https://link.springer.com/chapter/10.1007/978-3-031-35248-5_14", "body": "Because the medical image is so large, it must be compressed utilizing diverse machine learning and deep learning approaches while preserving the regions of interest. In , a combined lossy and lossless compression as a hybrid method using discrete walvet transform and recurrent neural network on brain images exactly like CT and MRI image. Thus ..."}, {"title": "Medical Image Analysis Using Machine Learning and Deep ... - Springer", "href": "https://link.springer.com/chapter/10.1007/978-981-19-4189-4_10", "body": "The DL follows a hierarchical order where the data of the input layer is transformed into a more abstract level to feed into the next level of the hierarchy. The DL uses a plethora of classifiers comprising Recurrent Neural Network (RNN), Convolutional Neural Network (CNN), Boltzmann machine, autoencoders, and Deep Belief Network (DBN)."}, {"title": "Recurrent Neural Networks in Medical Data Analysis and ... - ResearchGate", "href": "https://www.researchgate.net/publication/301244363_Recurrent_Neural_Networks_in_Medical_Data_Analysis_and_Classifications", "body": "Abstract. This chapter discusses dynamical neural network architectures for the classification of medical data. Various researches have indicated that recurrent neural networks such as the Elman ..."}]