Welcome to the InfoSci Platform
Multipath Convolutional Neural Network for Brain Tumor Detection (CNN)

Multipath Convolutional Neural Network for Brain Tumor Detection (CNN)

Mukesh Kumar Chandrakar, Anup Mishra, Arun Kumar
Copyright: © 2023 |Pages: 16
ISBN13: 9781799888925|ISBN10: 1799888924|ISBN13 Softcover: 9781799888932|EISBN13: 9781799888949
DOI: 10.4018/978-1-7998-8892-5.ch019
Cite Chapter Cite Chapter

MLA

Chandrakar, Mukesh Kumar, et al. "Multipath Convolutional Neural Network for Brain Tumor Detection (CNN)." Handbook of Research on Computer Vision and Image Processing in the Deep Learning Era, edited by A. Srinivasan, IGI Global, 2023, pp. 293-308. https://doi.org/10.4018/978-1-7998-8892-5.ch019

APA

Chandrakar, M. K., Mishra, A., & Kumar, A. (2023). Multipath Convolutional Neural Network for Brain Tumor Detection (CNN). In A. Srinivasan (Ed.), Handbook of Research on Computer Vision and Image Processing in the Deep Learning Era (pp. 293-308). IGI Global. https://doi.org/10.4018/978-1-7998-8892-5.ch019

Chicago

Chandrakar, Mukesh Kumar, Anup Mishra, and Arun Kumar. "Multipath Convolutional Neural Network for Brain Tumor Detection (CNN)." In Handbook of Research on Computer Vision and Image Processing in the Deep Learning Era, edited by A. Srinivasan, 293-308. Hershey, PA: IGI Global, 2023. https://doi.org/10.4018/978-1-7998-8892-5.ch019

Export Reference

Mendeley
Favorite

Abstract

Brain tumor segmentation is a new automated medical image diagnosis application. A robust strategy to brain tumor segmentation and detection is an ongoing research problem, and the performance metrics of present tumor detection systems are little understood. Deep neural networks employing convolution neural networks (CNN) are being investigated in this regard; however, no generic architecture that can be employed as a robust technique for brain tumor diagnosis has been discovered. The authors have suggested a multipath CNN architecture for brain tumor segmentation and identification that outperforms existing approaches. The proposed work has been tested for datasets BRATS2013, BRTAS2015, and BRATS2017 with significant improvement in dice index and timing values by utilizing the capability of multipath CNN architecture, which combines both local and global paths. It was the objective to provide a simple and reliable method to determine segmentation and detection of brain tumor using brain tumor interface techniques (BCI).

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.