Hierarchical based tumor segmentation by detection using deep learning approach

Hierarchical based tumor segmentation by detection using deep learning approach Madona B Sahaai G R Jothilakshmi Abstract Brain tumor is a cluster of abnormal cells that grows out of control in brain. Identifying brain tumor is challenging for doctors, since its impact will lead to danger for human life. Spotting of brain tumor using traditional methods is not accurate. Deep learning provides solution for detecting Brain Tumor in an efficient way. We have used MRI scan images. Since the image contains noise, image pre-processing work has been done to enhance the images. Deep learning methods for images works with Convolutional Neural Network (CNN). CNN has an advantage of extracting features by own. CNN has many hidden layers, where features are extracted and those features are learned for future prediction process. Single Shot Detector is used for detection of tumor region. SSD uses 8732 default bounding boxes mapped to the ground truth boxes for localisation process. Jaccard Overlap is used for match the default box with ground truth box. The detected whole tumor region is then used for segmenting the proper tumor region.
05 01 2021 012080 http://dx.doi.org/10.1088/crossmark-policy iopscience.iop.org Hierarchical based tumor segmentation by detection using deep learning approach Journal of Physics: Conference Series paper Published under licence by IOP Publishing Ltd http://creativecommons.org/licenses/by/3.0/ https://iopscience.iop.org/info/page/text-and-data-mining 10.1088/1742-6596/1921/1/012080 https://iopscience.iop.org/article/10.1088/1742-6596/1921/1/012080 https://iopscience.iop.org/article/10.1088/1742-6596/1921/1/012080/pdf https://iopscience.iop.org/article/10.1088/1742-6596/1921/1/012080 https://iopscience.iop.org/article/10.1088/1742-6596/1921/1/012080/pdf https://iopscience.iop.org/article/10.1088/1742-6596/1921/1/012080/pdf https://iopscience.iop.org/article/10.1088/1742-6596/1921/1/012080/pdf https://iopscience.iop.org/article/10.1088/1742-6596/1921/1/012080 https://iopscience.iop.org/article/10.1088/1742-6596/1921/1/012080 https://iopscience.iop.org/article/10.1088/1742-6596/1921/1/012080/pdf Sobhaninia 2018 Brain tumor segmentation using deep learning by type specific sorting of images arxiv Siar 363 2019 Brain tumor detection using deep neural network and machine learning algorithm Kumar 2019 A deep learning for brain tumor MRI images semantic segmentation using FCN Sajid 2019 10.1007/s13369-019-03967-8 Brain tumor detection and segmentation in MR images using deep learning Tamije Selvy 169 2019 Brain tumor detection using deep learning techniques Nasor 158 2018 MRI tumor detection and localization by multiple threshold object counting technique Noreen 2020 10.1109/ACCESS.2020.2978629 A Deep learning model based on concatenation approach for diagnosis of brain tumor Thaha 2019 10.1007/s10916-019-1416-0 Brain tumor segmentation using convolutional neural networks in MRI images Sultan 2019 10.1109/ACCESS.2019.2919122 Multi-Classification of brain tumor images using deep neural network Huang 2020 10.1109/ACCESS.2020.2993618 Convolutional neural network based on complex networks for brain tumor image classification with modified activation function Khan Swati 2019 Content-based brain tumor retrieval for MR images using transfer learning Ali 2020 Brain tumor image segmentation using deep networks Abdel-Gawad 2020 10.1109/ACCESS.2020.3009898 Optimized edge detection technique for brain tumor detection in MR images Zhu 2020 10.1109/ACCESS.2020.2972562 Moving object detection with deep CNNs Li 2019 10.1109/ACCESS.2019.2958370 Brain tumor detection based on multimodal information fusion and convolutional neural network