Survey on the Techniques for Classification and Identification of Brain Tumour Types from MRI Images Using Deep Learning Algorithms

Author:

K. Gayathri Devi1,Balasubramanian Kishore2

Affiliation:

1. Department of ECE, Dr. N.G.P. Institute of Technology, Coimbatore, Tamil Nadu 641048, India

2. Department of EEE, Dr. Mahalingam College of Engineering and Technology, Pollachi, Tamil Nadu 642003, India

Abstract

Abstract: A tumour is an uncontrolled growth of tissues in any part of the body. Tumours are of different types and characteristics and have different treatments. Detection of a tumour in the earlier stages makes the treatment easier. Scientists and researchers have been working towards developing sophisticated techniques and methods for identifying the form and stage of tumours. This paper provides a systematic literature survey of techniques for brain tumour segmentation and classification of abnormality and normality from MRI images based on different methods including deep learning techniques. This survey covers publicly available datasets, enhancement techniques, segmentation, feature extraction, and the classification of three different types of brain tumours that include gliomas, meningioma, and pituitary and deep learning algorithms implemented for brain tumour analysis. Finally, this survey provides all the important literature on the detection of brain tumours with their developments.

Publisher

Bentham Science Publishers Ltd.

Subject

General Computer Science

Reference56 articles.

1. Rao V.; Sarabi M S; Jaiswal a; Brain tumor segmentation with deep learning. MICCAI Multimodal Brain Tumor Segmentation Challenge (BraTS) Munich: Springer International Publishing 2015,56-59

2. Işın A.; Direkoğlu C.; Şah M.; Review of MRI-based brain tumor image segmentation using deep learning methods. Procedia Comput Sci 2016,102,317-324

3. Moeskops P.; Deep learning for multi-task medical image segmentation in multiple modalities MICCAI, Springer International Publishing: Cham 2016,478-486

4. Kamnitsas K.; DeepMedic for Brain Tumor Segmentation Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries 2016,138-149

5. Hao X.; Wu Y.; Song G.; Li Z.; Fan Y.; Zhang Y.; Brain tumor segmentation using a fully convolutional neural network with conditional random fields International workshop on brain lesion: glioma, multiple sclerosis, stroke and traumatic brain injuries Springer 2016,75-87

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