Dense-PSP-UNet: A neural network for fast inference liver ultrasound segmentation
<p dir="ltr">Liver Ultrasound (US) or sonography is popularly used because of its real-time output, low-cost, ease-ofuse, portability, and non-invasive nature. Segmentation of real-time liver US is essential for diagnosing and analyzing liver conditions (e.g., hepatocellular carcinom...
محفوظ في:
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| مؤلفون آخرون: | , , |
| منشور في: |
2023
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| _version_ | 1864513543618953216 |
|---|---|
| author | Mohammed Yusuf Ansari (16904523) |
| author2 | Yin Yang (35103) Pramod Kumar Meher (17316988) Sarada Prasad Dakua (14151789) |
| author2_role | author author author |
| author_facet | Mohammed Yusuf Ansari (16904523) Yin Yang (35103) Pramod Kumar Meher (17316988) Sarada Prasad Dakua (14151789) |
| author_role | author |
| dc.creator.none.fl_str_mv | Mohammed Yusuf Ansari (16904523) Yin Yang (35103) Pramod Kumar Meher (17316988) Sarada Prasad Dakua (14151789) |
| dc.date.none.fl_str_mv | 2023-02-01T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.compbiomed.2022.106478 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Dense-PSP-UNet_A_neural_network_for_fast_inference_liver_ultrasound_segmentation/24474637 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biomedical and clinical sciences Clinical sciences Engineering Biomedical engineering Information and computing sciences Artificial intelligence Data management and data science Liver segmentation Ultrasound segmentation Multiscale features Real-time segmentation |
| dc.title.none.fl_str_mv | Dense-PSP-UNet: A neural network for fast inference liver ultrasound segmentation |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Liver Ultrasound (US) or sonography is popularly used because of its real-time output, low-cost, ease-ofuse, portability, and non-invasive nature. Segmentation of real-time liver US is essential for diagnosing and analyzing liver conditions (e.g., hepatocellular carcinoma (HCC)), assisting the surgeons/radiologists in therapeutic procedures. In this paper, we propose a method using a modified Pyramid Scene Parsing (PSP) module in tuned neural network backbones to achieve real-time segmentation without compromising the segmentation accuracy. Considering widespread noise in US data and its impact on outcomes, we study the impact of pre-processing and the influence of loss functions on segmentation performance. We have tested our method after annotating a publicly available US dataset containing 2400 images of 8 healthy volunteers (link to the annotated dataset is provided); the results show that the Dense-PSP-UNet model achieves a high Dice coefficient of 0.913±0.024 while delivering a real-time performance of 37 frames per second (FPS).</p><h2>Other Information</h2><p dir="ltr">Published in: Computers in Biology and Medicine<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.compbiomed.2022.106478" target="_blank">https://dx.doi.org/10.1016/j.compbiomed.2022.106478</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_ce3aa5fdd9cd929a88ae81b5cc3b0929 |
| identifier_str_mv | 10.1016/j.compbiomed.2022.106478 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24474637 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Dense-PSP-UNet: A neural network for fast inference liver ultrasound segmentationMohammed Yusuf Ansari (16904523)Yin Yang (35103)Pramod Kumar Meher (17316988)Sarada Prasad Dakua (14151789)Biomedical and clinical sciencesClinical sciencesEngineeringBiomedical engineeringInformation and computing sciencesArtificial intelligenceData management and data scienceLiver segmentationUltrasound segmentationMultiscale featuresReal-time segmentation<p dir="ltr">Liver Ultrasound (US) or sonography is popularly used because of its real-time output, low-cost, ease-ofuse, portability, and non-invasive nature. Segmentation of real-time liver US is essential for diagnosing and analyzing liver conditions (e.g., hepatocellular carcinoma (HCC)), assisting the surgeons/radiologists in therapeutic procedures. In this paper, we propose a method using a modified Pyramid Scene Parsing (PSP) module in tuned neural network backbones to achieve real-time segmentation without compromising the segmentation accuracy. Considering widespread noise in US data and its impact on outcomes, we study the impact of pre-processing and the influence of loss functions on segmentation performance. We have tested our method after annotating a publicly available US dataset containing 2400 images of 8 healthy volunteers (link to the annotated dataset is provided); the results show that the Dense-PSP-UNet model achieves a high Dice coefficient of 0.913±0.024 while delivering a real-time performance of 37 frames per second (FPS).</p><h2>Other Information</h2><p dir="ltr">Published in: Computers in Biology and Medicine<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.compbiomed.2022.106478" target="_blank">https://dx.doi.org/10.1016/j.compbiomed.2022.106478</a></p>2023-02-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.compbiomed.2022.106478https://figshare.com/articles/journal_contribution/Dense-PSP-UNet_A_neural_network_for_fast_inference_liver_ultrasound_segmentation/24474637CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/244746372023-02-01T00:00:00Z |
| spellingShingle | Dense-PSP-UNet: A neural network for fast inference liver ultrasound segmentation Mohammed Yusuf Ansari (16904523) Biomedical and clinical sciences Clinical sciences Engineering Biomedical engineering Information and computing sciences Artificial intelligence Data management and data science Liver segmentation Ultrasound segmentation Multiscale features Real-time segmentation |
| status_str | publishedVersion |
| title | Dense-PSP-UNet: A neural network for fast inference liver ultrasound segmentation |
| title_full | Dense-PSP-UNet: A neural network for fast inference liver ultrasound segmentation |
| title_fullStr | Dense-PSP-UNet: A neural network for fast inference liver ultrasound segmentation |
| title_full_unstemmed | Dense-PSP-UNet: A neural network for fast inference liver ultrasound segmentation |
| title_short | Dense-PSP-UNet: A neural network for fast inference liver ultrasound segmentation |
| title_sort | Dense-PSP-UNet: A neural network for fast inference liver ultrasound segmentation |
| topic | Biomedical and clinical sciences Clinical sciences Engineering Biomedical engineering Information and computing sciences Artificial intelligence Data management and data science Liver segmentation Ultrasound segmentation Multiscale features Real-time segmentation |