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 Addressing the complexities of postoperative brain MRI cavity segmentationa comprehensive review Subject The topic of the resource Deep learning models; Fine-tuning and enhancement; Magnetic resonance images; Postoperative brain; Segmentation; U-net architectures Description An account of the resource Postoperative brain magnetic resonance images (MRI) is pivotal for evaluating tumor resection and monitoring post-surgical changes. The segmentation of surgical cavities in these images poses challenges due to artifacts, tissue reorganization, and heterogeneous appearances. This study explores challenges and advancements in postoperative brain MRI segmentation, examining publicly accessible datasets and the efficacy of various deep learning models. The analysis focuses on different U-Net models (U-Net, V-Net, ResU-Net, attention U-Net, dense U-Net, and dilated U-Net) using the EPISURG dataset. The training dice scores are as follows: U-Net 0.8150, attention U-Net 0.8534, V-Net 0.7602, ResU-Net 0.7945, dense U-Net 0.83, dilated U-Net 0.80. The study thoroughly assesses existing postoperative cavity segmentation models and proposes a fine-tuning approach to enhance the performance further, particularly for the best-performing model, attention U-Net. This fine-tuning involves introducing dilated convolutions and residual connections to the existing attention U-Net model, resulting in improved results. These improvements underscore the necessity for ongoing research to select and adapt efficient models, retrain specific layers with a comprehensive collection of postoperative images, and fine-tune model parameters to enhance feature extraction during the encoding phase. 2024, Institute of Advanced Engineering and Science. All rights reserved. Creator An entity primarily responsible for making the resource Sobha X.P.; Sathish P.K.; Raju G. Source A related resource from which the described resource is derived Bulletin of Electrical Engineering and Informatics, Vol-13, No. 5, pp. 3463-3469. Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/eei.v13i5.7930" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/eei.v13i5.7930</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200418089&amp;doi=10.11591%2Feei.v13i5.7930&amp;partnerID=40&amp;md5=ead9b11e25feb87a1b14e3a906d1dbdb" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200418089&amp;doi=10.11591%2feei.v13i5.7930&amp;partnerID=40&amp;md5=ead9b11e25feb87a1b14e3a906d1dbdb</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 20893191 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 Sobha X.P., Department of Computer Science, School of Engineering and Technology, Christ University, Karnataka, Bengaluru, India, Department of Computer Science, Jyothi Engineering College, Cheruthuruthy, Kerala, Thrissur, India; Sathish P.K., Department of Computer Science, School of Engineering and Technology, Christ University, Karnataka, Bengaluru, India; Raju G., Department of Computer Science, School of Engineering and Technology, Christ University, Karnataka, Bengaluru, India