Hepato Web App for Classification and Segmentation of Liver Lesions in CT Scans Using EFF Net Article Swipe
Ms Rahana Sulthana
,
Masanobu Shabana
,
M DIVYA
,
Fabián N. Murrieta-Rico
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48175/ijarsct-8633d
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48175/ijarsct-8633d
The liver is a large organ situated in the upper right section of the abdomen, located beneath the diaphragm and above the stomach. Liver cancer is a type of cancer that originates in the liver, resulting from uncontrolled cell growth. Computed tomography (CT scan or CAT scan) is a non-invasive imaging technique that integrates x-rays with computer technology. CT scans are essential for diagnosing liver cancer in patients. A cascaded model of convolutional neural networks is employed to segment the liver, while an efficient net is used to detect liver lesions from CT scans. This method achieves an outstanding accuracy of 0.998 for both liver segmentation and liver lesion detection
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- https://doi.org/10.48175/ijarsct-8633d
- OA Status
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- References
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https://doi.org/10.48175/ijarsct-8633dDigital Object Identifier
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Hepato Web App for Classification and Segmentation of Liver Lesions in CT Scans Using EFF NetWork title
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articleOpenAlex work type
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enPrimary language
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2024Year of publication
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2024-10-30Full publication date if available
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Ms Rahana Sulthana, Masanobu Shabana, M DIVYA, Fabián N. Murrieta-RicoList of authors in order
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https://doi.org/10.48175/ijarsct-8633dPublisher landing page
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://doi.org/10.48175/ijarsct-8633dDirect OA link when available
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Segmentation, Computer science, Web application, Artificial intelligence, Medicine, Pattern recognition (psychology), Nuclear medicine, World Wide WebTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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