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 Conference Papers Conference Paper Faculty Publications- Conference Papers 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 Automated Fetal Brain Localization, Segmentation, and Abnormalities Detection Through Random Sample Consensus Subject The topic of the resource Abnormalities; Automatic; Fetal MRI; Head localization; Machine learning; Random sample consensus (RANSAC); Region of interest (ROI); Segmentation Description An account of the resource The ability to detect and identify prenatal brain abnormalities using magnetic resonance imaging (MRI) is critical, as one in every 1000 women is pregnant with one. The brain is abnormal. Detection of embryonic brain abnormalities at an early stage machine learning techniques can help you increase the quality of your data. Treatment planning and diagnosis according to the literature that the majority of the research done in order to classify brain abnormalities in the term "very early age" refers to preterm newborns and neonates, not fetal development. However, studies of prenatal brain MRI imaging have been published and compared these images to the MRI scans of newborns to identify a non-fetal aberrant behavior in neonates. In this case, a pipeline procedure, on the other hand, is time-consuming. In this research, a machine learning-based pipeline process for fetal brain categorization (FBC) is proposed. The classification of fetal brain anomalies at an early stage, before the baby is delivered, is the paper's key contribution. The proposed approach uses a flexible and simple method with cheap processing cost to detect and categorize a variety of abnormalities from MRI images with a wide range of fetal gestational age (GA). Segmentation, augmentation, feature extraction, and classification and detecting anomalies of the fbrain are different phases of the recent method. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Vijayalakshmi S.; Durgadevi P.; Gayathri S.P.; Shariff A.S.M. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 495-504. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-19-2211-4_44" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_44</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135011565&amp;doi=10.1007%2F978-981-19-2211-4_44&amp;partnerID=40&amp;md5=b0d5261998bcf710bca47ce418676e44" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135011565&amp;doi=10.1007%2f978-981-19-2211-4_44&amp;partnerID=40&amp;md5=b0d5261998bcf710bca47ce418676e44</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981192210-7 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 Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Vijayalakshmi S., Christ University, Bangalore, India; Durgadevi P., Galgotias College of Engineering and Technology, Greater Noida, India; Gayathri S.P., Gandhigram Rural Institute (Deemed to be University), Dindigul, India; Shariff A.S.M., Galgotias College of Engineering and Technology, Greater Noida, India