Publication:
Pelvic Tumor Segmentation in MRI Images Using Deep Learning with DeepLabV3+ and U-Net: A Performance Comparison

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Issued Date

2024-01-01

Resource Type

Conference Paper

DOI

10.1109/BMEiCON64021.2024.10896343

Scopus ID

2-s2.0-105000417050

Journal Title

16th Biomedical Engineering International Conference, BMEiCON 2024

Rights Holder(s)

SCOPUS

Bibliographic Citation

16th Biomedical Engineering International Conference, BMEiCON 2024 (2024)

Suggested Citation

Pelvic Tumor Segmentation in MRI Images Using Deep Learning with DeepLabV3+ and U-Net: A Performance Comparison. 16th Biomedical Engineering International Conference, BMEiCON 2024 (2024). doi:10.1109/BMEiCON64021.2024.10896343 Retrieved from: https://hdl.handle.net/20.500.14740/20172

Title

Pelvic Tumor Segmentation in MRI Images Using Deep Learning with DeepLabV3+ and U-Net: A Performance Comparison

Author's Affiliation

Srinakharinwirot University

Corresponding Author(s)

Nobnop N.

Other Contributor(s)

Srinakharinwirot University

Keyword(s)

Physics and Astronomy
 Engineering
 Computer Science

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URI

https://hdl.handle.net/20.500.14740/20172

Collections

Scopus: Year 2024

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