Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Novel Generative Adversarial Network-Based Approach for Automated Brain Tumour Segmentation Subject The topic of the resource autoencoder; brain MRI; deep learning; generative adversarial learning; tumour segmentation Description An account of the resource Background: Medical image segmentation is more complicated and demanding than ordinary image segmentation due to the density of medical pictures. A brain tumour is the most common cause of high mortality. Objectives: Extraction of tumorous cells is particularly difficult due to the differences between tumorous and non-tumorous cells. In ordinary convolutional neural networks, local background information is restricted. As a result, previous deep learning algorithms in medical imaging have struggled to detect anomalies in diverse cells. Methods: As a solution to this challenge, a deep convolutional generative adversarial network for tumour segmentation from brain Magnetic resonance Imaging (MRI) images is proposed. A generator and a discriminator are the two networks that make up the proposed model. This network focuses on tumour localisation, noise-related issues, and social class disparities. Results: Dice Score Coefficient (DSC), Peak Signal to Noise Ratio (PSNR), and Structural Index Similarity (SSIM) are all generally 0.894, 62.084 dB, and 0.88912, respectively. The models accuracy has improved to 97 percent, and its loss has reduced to 0.012. Conclusions: Experiments reveal that the proposed approach may successfully segment tumorous and benign tissues. As a result, a novel brain tumour segmentation approach has been created. 2023 by the authors. Creator An entity primarily responsible for making the resource Sille R.; Choudhury T.; Sharma A.; Chauhan P.; Tomar R.; Sharma D. Source A related resource from which the described resource is derived Medicina (Lithuania), Vol-59, No. 1 Publisher An entity responsible for making the resource available MDPI Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.3390/medicina59010119" target="_blank" rel="noreferrer noopener">https://doi.org/10.3390/medicina59010119</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146771972&amp;doi=10.3390%2Fmedicina59010119&amp;partnerID=40&amp;md5=2be2250c4cfaf823c6d410dc8969b672" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146771972&amp;doi=10.3390%2fmedicina59010119&amp;partnerID=40&amp;md5=2be2250c4cfaf823c6d410dc8969b672</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Relation A related resource ISSN: 1010660X; PubMed ID: 36676743 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Sille R., School of Computer Science, University of Petroleum and Energy Studies (UPES), Dehradun, 248007, India; Choudhury T., School of Computer Science, University of Petroleum and Energy Studies (UPES), Dehradun, 248007, India; Sharma A., School of Computer Science, University of Petroleum and Energy Studies (UPES), Dehradun, 248007, India; Chauhan P., School of Computer Science, University of Petroleum and Energy Studies (UPES), Dehradun, 248007, India; Tomar R., Persistent Systems, India, 411057, India; Sharma D., School of Business and Management, CHRIST University, Bangalore, 560074, India