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#6242. mCA-Net: modified comprehensive attention convolutional neural network for skin lesion segmentation
| September 2026 | publication date |
| Proposal available till | 18-05-2025 |
| 4 total number of authors per manuscript | 0 $ |
| The title of the journal is available only for the authors who have already paid for |
| Journal’s subject area: |
| Medicine |
| place 1 | place 2 | place 3 | place 4 |
| Free | Free | Free | Free |
| 2350 $ | 1200 $ | 1050 $ | 900 $ |
Contract №6242.1   | Contract №6242.2 | Contract №6242.3 | Contract №6242.4 |
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Abstract:
Skin is the first line of defense of the human body. Because the skin is exposed to the outside and suffersvarious aggressions, Skin cancer is the most common cancer. Accurate skin lesions image segmentation is essential for skin disease diagnosis and treatment planning. In order toimprove the segmentation results of the recently proposed comprehensive attention convolutional neural network(CA-Net) for skin lesions image segmentation, In this work, we propose a modified medical image segmentation network—modified comprehensive attention convolutional neural network (mCA-Net) to further improve segmentation performance. In particular, we create a new multi-scale channel attention module—MS-CA, which can display more accurate and relevant feature channels on multiple scales.
Keywords:
attention; melanoma; Timage segmentation
Contacts :
2 place - free (for sale)
3 place - free (for sale)
4 place - free (for sale)
Abstract:
Skin is the first line of defense of the human body. Because the skin is exposed to the outside and suffersvarious aggressions, Skin cancer is the most common cancer. Accurate skin lesions image segmentation is essential for skin disease diagnosis and treatment planning. In order toimprove the segmentation results of the recently proposed comprehensive attention convolutional neural network(CA-Net) for skin lesions image segmentation, In this work, we propose a modified medical image segmentation network—modified comprehensive attention convolutional neural network (mCA-Net) to further improve segmentation performance. In particular, we create a new multi-scale channel attention module—MS-CA, which can display more accurate and relevant feature channels on multiple scales.
Keywords:
attention; melanoma; Timage segmentation
Contacts :
