Browsing by Author "Muhammad Waqas Nadeem"

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    Deep learning based architecture to predict survival time of brain tumor patients
    (UMT.Lahore, 2019) Muhammad Waqas Nadeem
    Deep learning algorithms enable computational models consist of multiple processing layers for the presentation of data with multiple levels of abstraction. In recent years, usage of deep learning is rapidly proliferating in medical image processing, medical image analysis and bioinformatics. Consequently, deep learning dramatically changed and improved the way of recognition, predication, and diagnosis effectively in numerous areas of healthcare such as, pathology, brain tumor, lungs cancer, abdomen, cardiac, retina and so on. Convolution neural network has great impact in the field of image segmentation and classification. The positional relation between the features may be disregard by the traditional CNN with max-pooling function. Capsule network has the dynamic routing between the network layers that efficiently finds the relation of features. The capsule network with inception block proposed that gives the dynamic kernel size to achieve the state-of-art accuracy for the prediction of survival time for the brain tumor patients