Improved UNet Deep Learning Model for Automatic Detection of Lung Cancer Nodules Article Swipe
Vinay Kumar
,
Baraa Riyadh Altahan
,
Tariq Rasheed
,
Prabhdeep Singh
,
Devpriya Soni
,
Hashem O. Alsaab
,
Fardin Ahmadi
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1155/2023/9739264
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1155/2023/9739264
Uncontrolled cell growth in the two spongy lung organs in the chest is the most prevalent kind of cancer. When cells from the lungs spread to other tissues and organs, this is referred to as metastasis. This work uses image processing, deep learning, and metaheuristics to identify cancer in its early stages. At this point, a new convolutional neural network is constructed. The predator technique has the potential to increase network architecture and accuracy. Deep learning identified lung cancer spinal metastases in as energy consumption increased CT readings for lung cancer bone metastases decreased. Qualified physicians, on the other hand, discovered 71.14 and 74.60 percent of targets with energies of 140 and 60 keV, respectively, whereas the proposed model gives 76.51 and 81.58 percent, respectively. Expert physicians’ detection rate was 74.60 percent lower than deep learning’s detection rate of 81.58 percent. The proposed method has the highest accuracy, sensitivity, and specificity (93.4, 98.4, and 97.1 percent, respectively), as well as the lowest error rate (1.6 percent). Finally, in lung segmentation, the proposed model outperforms the CNN model. High‐intensity energy‐spectral CT images are more difficult to segment than low‐intensity energy‐spectral CT images.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1155/2023/9739264
- https://downloads.hindawi.com/journals/cin/2023/9739264.pdf
- OA Status
- hybrid
- Cited By
- 22
- References
- 37
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4318540886
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4318540886Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1155/2023/9739264Digital Object Identifier
- Title
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Improved UNet Deep Learning Model for Automatic Detection of Lung Cancer NodulesWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-01-01Full publication date if available
- Authors
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Vinay Kumar, Baraa Riyadh Altahan, Tariq Rasheed, Prabhdeep Singh, Devpriya Soni, Hashem O. Alsaab, Fardin AhmadiList of authors in order
- Landing page
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https://doi.org/10.1155/2023/9739264Publisher landing page
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https://downloads.hindawi.com/journals/cin/2023/9739264.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://downloads.hindawi.com/journals/cin/2023/9739264.pdfDirect OA link when available
- Concepts
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Lung cancer, Deep learning, Convolutional neural network, Artificial intelligence, Computer science, Lung, Segmentation, Cancer, Metastasis, Medicine, Radiology, Pattern recognition (psychology), Pathology, Internal medicineTop concepts (fields/topics) attached by OpenAlex
- Cited by
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22Total citation count in OpenAlex
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2025: 9, 2024: 10, 2023: 3Per-year citation counts (last 5 years)
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37Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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