Deep learning models and traditional automated techniques for brain tumor segmentation in MRI: a review.
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| Title: | Deep learning models and traditional automated techniques for brain tumor segmentation in MRI: a review. |
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| Authors: | Jyothi, Parvathy1, parvathyjyothi@gmail.com, Singh, A. Robert2 |
| Source: | Artificial Intelligence Review; Apr2023, Vol. 56 Issue 4, p2923-2969, 47p |
| Database: | Applied Science & Technology Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 162392938 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=162392938 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10462-022-10245-x Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 47 StartPage: 2923 Titles: – TitleFull: Deep learning models and traditional automated techniques for brain tumor segmentation in MRI: a review. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jyothi, Parvathy – PersonEntity: Name: NameFull: Singh, A. Robert IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2023 Type: published Y: 2023 Identifiers: – Type: issn-print Value: 02692821 Numbering: – Type: volume Value: 56 – Type: issue Value: 4 Titles: – TitleFull: Artificial Intelligence Review Type: main |
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