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Conference Paper/Proceeding/Abstract 75 views 29 downloads

Texture Feature Analysis for Classification of Early-Stage Prostate Cancer in MpMRI

Asmail Muftah Orcid Logo, Sophie Shermer Orcid Logo, Frank C. Langbein Orcid Logo

Lecture Notes in Computer Science, Volume: 14976, Pages: 118 - 131

Swansea University Author: Sophie Shermer Orcid Logo

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DOI (Published version): 10.1007/978-3-031-67285-9_9

Published in: Lecture Notes in Computer Science
ISBN: 9783031672842 9783031672859
ISSN: 0302-9743 1611-3349
Published: Cham Springer Nature Switzerland 2024
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa68714
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title Texture Feature Analysis for Classification of Early-Stage Prostate Cancer in MpMRI
spellingShingle Texture Feature Analysis for Classification of Early-Stage Prostate Cancer in MpMRI
Sophie Shermer
title_short Texture Feature Analysis for Classification of Early-Stage Prostate Cancer in MpMRI
title_full Texture Feature Analysis for Classification of Early-Stage Prostate Cancer in MpMRI
title_fullStr Texture Feature Analysis for Classification of Early-Stage Prostate Cancer in MpMRI
title_full_unstemmed Texture Feature Analysis for Classification of Early-Stage Prostate Cancer in MpMRI
title_sort Texture Feature Analysis for Classification of Early-Stage Prostate Cancer in MpMRI
author_id_str_mv 6ebef22eb31eafc75aedcf5bfe487777
author_id_fullname_str_mv 6ebef22eb31eafc75aedcf5bfe487777_***_Sophie Shermer
author Sophie Shermer
author2 Asmail Muftah
Sophie Shermer
Frank C. Langbein
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container_volume 14976
container_start_page 118
publishDate 2024
institution Swansea University
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9783031672859
issn 0302-9743
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doi_str_mv 10.1007/978-3-031-67285-9_9
publisher Springer Nature Switzerland
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published_date 2024-08-15T08:22:03Z
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