Effective texture features in mammogram images via multi-roi segmentation

Digital mammography increasingly necessitates image segmentation for the purpose of dividing mammograms into individual slices. For the purpose of removing suspicious masses or tumours from mammograms, this process is carried out using a region of interest (ROI). More training photos are needed for...

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Bibliographic Details
Published inMATEC web of conferences Vol. 392; p. 1136
Main Authors Prasad, K. Rajendra, Praveen Kumar, Chatakunta, Suneel, Sajja, Raghu Kumar, Lingamallu
Format Journal Article Conference Proceeding
LanguageEnglish
Published Les Ulis EDP Sciences 2024
Subjects
Digital imaging
Image classification
Image segmentation
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Summary:Digital mammography increasingly necessitates image segmentation for the purpose of dividing mammograms into individual slices. For the purpose of removing suspicious masses or tumours from mammograms, this process is carried out using a region of interest (ROI). More training photos are needed for mammography image classification, and these circumstances, ROI requires more processing time. The temporal complexity difficulties with the suggested multi-ROI method are the subject of this article. To show how effective the suggested multi-ROI is compared to the current segmentation approach, experiments are conducted on benchmarked datasets.
Bibliography:ObjectType-Conference Proceeding-1
SourceType-Conference Papers & Proceedings-1
content type line 21
ISSN:2261-236X
2274-7214
2261-236X
DOI:10.1051/matecconf/202439201136