Literature DB >> 28622675

State-of-the-Art Methods for Brain Tissue Segmentation: A Review.

Lingraj Dora, Sanjay Agrawal, Rutuparna Panda, Ajith Abraham.   

Abstract

Brain tissue segmentation is one of the most sought after research areas in medical image processing. It provides detailed quantitative brain analysis for accurate disease diagnosis, detection, and classification of abnormalities. It plays an essential role in discriminating healthy tissues from lesion tissues. Therefore, accurate disease diagnosis and treatment planning depend merely on the performance of the segmentation method used. In this review, we have studied the recent advances in brain tissue segmentation methods and their state-of-the-art in neuroscience research. The review also highlights the major challenges faced during tissue segmentation of the brain. An effective comparison is made among state-of-the-art brain tissue segmentation methods. Moreover, a study of some of the validation measures to evaluate different segmentation methods is also discussed. The brain tissue segmentation, content in terms of methodologies, and experiments presented in this review are encouraging enough to attract researchers working in this field.

Mesh:

Year:  2017        PMID: 28622675     DOI: 10.1109/RBME.2017.2715350

Source DB:  PubMed          Journal:  IEEE Rev Biomed Eng        ISSN: 1937-3333


  10 in total

1.  Multi-task learning approach for volumetric segmentation and reconstruction in 3D OCT images.

Authors:  Dheo A Y Cahyo; Ai Ping Yow; Seang-Mei Saw; Marcus Ang; Michael Girard; Leopold Schmetterer; Damon Wong
Journal:  Biomed Opt Express       Date:  2021-11-08       Impact factor: 3.732

2.  Co-optimization Learning Network for MRI Segmentation of Ischemic Penumbra Tissues.

Authors:  Liangliang Liu; Jing Zhang; Jin-Xiang Wang; Shufeng Xiong; Hui Zhang
Journal:  Front Neuroinform       Date:  2021-12-16       Impact factor: 4.081

Review 3.  Machine learning in neuro-oncology: toward novel development fields.

Authors:  Vincenzo Di Nunno; Mario Fordellone; Giuseppe Minniti; Sofia Asioli; Alfredo Conti; Diego Mazzatenta; Damiano Balestrini; Paolo Chiodini; Raffaele Agati; Caterina Tonon; Alicia Tosoni; Lidia Gatto; Stefania Bartolini; Raffaele Lodi; Enrico Franceschi
Journal:  J Neurooncol       Date:  2022-06-28       Impact factor: 4.506

4.  LLRHNet: Multiple Lesions Segmentation Using Local-Long Range Features.

Authors:  Liangliang Liu; Ying Wang; Jing Chang; Pei Zhang; Gongbo Liang; Hui Zhang
Journal:  Front Neuroinform       Date:  2022-05-05       Impact factor: 3.739

Review 5.  Review on Hybrid Segmentation Methods for Identification of Brain Tumor in MRI.

Authors:  Khurram Ejaz; Mohd Shafry Mohd Rahim; Muhammad Arif; Diana Izdrui; Daniela Maria Craciun; Oana Geman
Journal:  Contrast Media Mol Imaging       Date:  2022-07-11       Impact factor: 3.009

6.  Discovery and visualization of structural biomarkers from MRI using transport-based morphometry.

Authors:  Shinjini Kundu; Soheil Kolouri; Kirk I Erickson; Arthur F Kramer; Edward McAuley; Gustavo K Rohde
Journal:  Neuroimage       Date:  2017-11-05       Impact factor: 6.556

7.  MhURI:A Supervised Segmentation Approach to Leverage Salient Brain Tissues in Magnetic Resonance Images.

Authors:  Palash Ghosal; Tamal Chowdhury; Amish Kumar; Ashok Kumar Bhadra; Jayasree Chakraborty; Debashis Nandi
Journal:  Comput Methods Programs Biomed       Date:  2020-11-12       Impact factor: 7.027

8.  Local Complexity Estimation Based Filtering Method in Wavelet Domain for Magnetic Resonance Imaging Denoising.

Authors:  Izlian Y Orea-Flores; Francisco J Gallegos-Funes; Alfonso Arellano-Reynoso
Journal:  Entropy (Basel)       Date:  2019-04-16       Impact factor: 2.524

9.  Towards an Architecture of a Multi-purpose, User-Extendable Reference Human Brain Atlas.

Authors:  Wieslaw L Nowinski
Journal:  Neuroinformatics       Date:  2021-11-26

10.  A deep learning method for automatic segmentation of the bony orbit in MRI and CT images.

Authors:  Jared Hamwood; Beat Schmutz; Michael J Collins; Mark C Allenby; David Alonso-Caneiro
Journal:  Sci Rep       Date:  2021-07-01       Impact factor: 4.379

  10 in total

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