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| Title: | Neural networks skin tumor diagnostic system | |
| Author (s): | Zhao Zhang Moss, Randy Hays Stoecker, W.V. | |
| Department/Lab Affiliations: | Electrical and Computer Engineering Image Processing Laboratory | |
| Keywords: | backpropagation backpropagation learning algorithm feature extraction malignant melanoma diagnostic system medical image processing neural nets neural networks skin tumor diagnostic system skin tumor images tumours | |
| Issue Date: | 2003 | |
| Publisher: | Institute of Electrical and Electronics Engineers | |
| Citation: | Zhao Zhang; Moss, R.H.; Stoecker, W.V., "Neural networks skin tumor diagnostic system" Proceedings of the 2003 International Conference on Neural Networks and Signal Processing, 2003. pp. 191- 192 Vol.1, 14-17 Dec. 2003 | |
| Abstract: | In this study, a malignant melanoma diagnostic system is designed using a straightforward neural network with the back-propagation learning algorithm. Eleven features are automatically extracted from skin tumor images. The correct diagnostic rate of this system is better than the average rate of 16 dermatologists who based their diagnosis with only the slide images. | |
| Type: | Article - Conference proceedings text | |
| Copyright Notice: | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. FULL COPYRIGHT INFORMATION: | |
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| Link to this page: | ||
| Full Text: |
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| title | Neural networks skin tumor diagnostic system | |
| contributor.author | Zhao Zhang | |
| contributor.author | Moss, Randy Hays | |
| contributor.author | Stoecker, W.V. | |
| contributor.deptlab | Electrical and Computer Engineering | |
| contributor.deptlab | Image Processing Laboratory | |
| subject | backpropagation | |
| subject | backpropagation learning algorithm | |
| subject | feature extraction | |
| subject | malignant melanoma diagnostic system | |
| subject | medical image processing | |
| subject | neural nets | |
| subject | neural networks | |
| subject | skin tumor diagnostic system | |
| subject | skin tumor images | |
| subject | tumours | |
| date.issued | 2003 | |
| date.submitted | 2007 | |
| publisher | Institute of Electrical and Electronics Engineers | |
| identifier.citation | Zhao Zhang; Moss, R.H.; Stoecker, W.V., "Neural networks skin tumor diagnostic system" Proceedings of the 2003 International Conference on Neural Networks and Signal Processing, 2003. pp. 191- 192 Vol.1, 14-17 Dec. 2003 | |
| identifier.pub.URI | ||
| description.abstract | In this study, a malignant melanoma diagnostic system is designed using a straightforward neural network with the back-propagation learning algorithm. Eleven features are automatically extracted from skin tumor images. The correct diagnostic rate of this system is better than the average rate of 16 dermatologists who based their diagnosis with only the slide images. | |
| type | Article - Conference proceedings | |
| type.DCMIType | text | |
| type.status | Final version | |
| rights | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. | |
| rights.URI | ||
| date.accessioned | 2007-04-05T14:19:18Z | |
| date.available | 2007-04-05T14:19:18Z | |
| identifier.persist.URI | ||
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