S Praveenkumar, T Kalaiselvi, Karuppanagounder Somasundaram
{"title":"Methods of Brain Extraction from Magnetic Resonance Images of Human Head: A Review.","authors":"S Praveenkumar, T Kalaiselvi, Karuppanagounder Somasundaram","doi":"10.1615/CritRevBiomedEng.2023047606","DOIUrl":null,"url":null,"abstract":"<p><p>Medical images are providing vital information to aid physicians in diagnosing a disease afflicting the organ of a human body. Magnetic resonance imaging is an important imaging modality in capturing the soft tissues of the brain. Segmenting and extracting the brain is essential in studying the structure and pathological condition of brain. There are several methods that are developed for this purpose. Researchers in brain extraction or segmentation need to know the current status of the work that have been done. Such an information is also important for improving the existing method to get more accurate results or to reduce the complexity of the algorithm. In this paper we review the classical methods and convolutional neural network-based deep learning brain extraction methods.</p>","PeriodicalId":53679,"journal":{"name":"Critical Reviews in Biomedical Engineering","volume":"51 4","pages":"1-40"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Critical Reviews in Biomedical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1615/CritRevBiomedEng.2023047606","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
Medical images are providing vital information to aid physicians in diagnosing a disease afflicting the organ of a human body. Magnetic resonance imaging is an important imaging modality in capturing the soft tissues of the brain. Segmenting and extracting the brain is essential in studying the structure and pathological condition of brain. There are several methods that are developed for this purpose. Researchers in brain extraction or segmentation need to know the current status of the work that have been done. Such an information is also important for improving the existing method to get more accurate results or to reduce the complexity of the algorithm. In this paper we review the classical methods and convolutional neural network-based deep learning brain extraction methods.
期刊介绍:
Biomedical engineering has been characterized as the application of concepts drawn from engineering, computing, communications, mathematics, and the physical sciences to scientific and applied problems in the field of medicine and biology. Concepts and methodologies in biomedical engineering extend throughout the medical and biological sciences. This journal attempts to critically review a wide range of research and applied activities in the field. More often than not, topics chosen for inclusion are concerned with research and practice issues of current interest. Experts writing each review bring together current knowledge and historical information that has led to the current state-of-the-art.