Abstract
This paper presents the detection of brain tumors through the YOLOv3 deep neural network model in a portable electromagnetic (EM) imaging system. YOLOv3 is a popular object detection model with high accuracy and improved computational speed. Initially, the scattering parameters are collected from the nine-antenna array setup with a tissue-mimicking head phantom, where one antenna acts as a transmitter and the other eight antennas act as receivers. The images are then reconstructed from the post-processed scattering parameters by applying the modified delay-multiply-and-sum algorithm that contains 416×416 pixels. Fifty sample images are collected from the different head regions through the EM imaging system. The images are later augmented to generate a final image data set for training, validation, and testing, where the data set contains 1000 images, including fifty samples with a single and double tumor. 80% of the images are utilized for training the network, whereas 10% are used for validation, and the rest 10% are utilized for testing purposes. The detection performance is investigated with the different image data sets. The achieved detection accuracy and F1 scores are 95.62% and 94.50%, respectively, which ensure better detection accuracy. The training accuracy and validation losses are 96.74% and 9.21%, respectively. The tumor detection with its location in different cases from the testing images is evaluated through YOLOv3, which demonstrates its potential in the portable electromagnetic head imaging system.
Highlights
Brain tumor is one of the major causes of mortality and disability because it invades the most vital organ of the human body
We present a deep neural network based YOLO version 3 (YOLOv3) algorithm to detect tumor with their location in the human brain
Since the YOLOv3 is a pre-trained model on MSCOCO (Microsoft Common Objects in Context) data set with 80 predefined classes, it uses darknet-53 convolutional neural network as a backbone of the model
Summary
Brain tumor is one of the major causes of mortality and disability because it invades the most vital organ of the human body. A brain tumor is the growth of abnormal cells that have formed inside the head. Brain cancer is the 10th leading cause of death due to tumors for men and women [1]. A high death percentage is caused due to the invasive properties of tumors. The standard imaging technologies to identify the tumor are computed tomography (CT) scans, MRI (magnetic resonance imaging) scanning, positron emission tomography (PET), ultrasound screening, and X-ray screening [2], [3]. The major pitfalls of the traditional imaging technologies are ionizing
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