A REVIEW ON RECENT TRENDS IN DEEP LEARNING METHODS FOR MEDICAL IMAGE ANALYSIS
DOI:
https://doi.org/10.61841/4eegb373Keywords:
MRI image,, --CT image,, Convolution neural network (CNN),, SVM and Multi-class Support vector machines (MCSVM),, ANN (Artificial Neural Networks), Deep learning techniques,, ,Stationary Wavelet Transform (SWT),, GCNN (Growing Convolution Neural NetworkAbstract
In this paper we are discussing about deep learning for medical image classification and analysis. First, we will discuss the importance of the deep learning and then the basic steps involved in deep learning. To evaluate tumours manually a very difficult task. Now a day’s in many applications medical image processing plays an important role. A significant increase was observed in medical cases associated with a brain tumour. MRI and CT images are mostly used to detect tumours and to examine abnormalities in terms of shape, size and location of the tumour. There are different techniques implemented for brain tumour diagnosis. Recent study focuses on 3D-based Convolution neural network (CNN), SVM and Multi-class Support vector machines (MCSVM), ANN (Artificial Neural Networks), for Deeper Segmentation.
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