Government of IndiaaDesigning an automated system for medical diagnosis
Author: Parekh, Ranjan
Keywords: Medical diagnosis
Medical offices--Automation
Issue Date: 2012-01
Publisher: National Council of Science Museums, Kolkata
Description: This paper proposes an automated system for recognizing disease conditions of human skin in context to health informatics. Skin texture images, displaying three dermatological skin conditions, are analyzed using a texture analysis technique, based on a set of normalized symmetrical Grey Level Occurrence Matrices (GLCM), and features are extracted from them using automated algorithms. The features are Jed to neural network classifiers for identification of the disease type. The features are considered in various combinations viz. individually, in joint 2-D and 3-D feature spaces, to find out the best recognition accuracies.
Description: Includes bibliographical references.
Source: National Council of Science Museums
Type: Article
Received From: National Council of Science Museums
| DC Field | Value |
| dc.contributor.author | Parekh, Ranjan |
| dc.date.accessioned | 2017-06-15T11:06:07Z |
| dc.date.available | 2017-06-15T11:06:07Z |
| dc.description | Includes bibliographical references. |
| dc.date.issued | 2012-01 |
| dc.description.abstract | This paper proposes an automated system for recognizing disease conditions of human skin in context to health informatics. Skin texture images, displaying three dermatological skin conditions, are analyzed using a texture analysis technique, based on a set of normalized symmetrical Grey Level Occurrence Matrices (GLCM), and features are extracted from them using automated algorithms. The features are Jed to neural network classifiers for identification of the disease type. The features are considered in various combinations viz. individually, in joint 2-D and 3-D feature spaces, to find out the best recognition accuracies. |
| dc.source | National Council of Science Museums |
| dc.format.extent | 57-64p.: col.ill. |
| dc.format.mimetype | application/pdf |
| dc.language.iso | en |
| dc.publisher | National Council of Science Museums, Kolkata |
| dc.subject | Medical diagnosis Medical offices--Automation |
| dc.type | Article |
| dc.identifier.issuenumber | 1 |
| dc.format.medium | text |
| DC Field | Value |
| dc.contributor.author | Parekh, Ranjan |
| dc.date.accessioned | 2017-06-15T11:06:07Z |
| dc.date.available | 2017-06-15T11:06:07Z |
| dc.description | Includes bibliographical references. |
| dc.date.issued | 2012-01 |
| dc.description.abstract | This paper proposes an automated system for recognizing disease conditions of human skin in context to health informatics. Skin texture images, displaying three dermatological skin conditions, are analyzed using a texture analysis technique, based on a set of normalized symmetrical Grey Level Occurrence Matrices (GLCM), and features are extracted from them using automated algorithms. The features are Jed to neural network classifiers for identification of the disease type. The features are considered in various combinations viz. individually, in joint 2-D and 3-D feature spaces, to find out the best recognition accuracies. |
| dc.source | National Council of Science Museums |
| dc.format.extent | 57-64p.: col.ill. |
| dc.format.mimetype | application/pdf |
| dc.language.iso | en |
| dc.publisher | National Council of Science Museums, Kolkata |
| dc.subject | Medical diagnosis Medical offices--Automation |
| dc.type | Article |
| dc.identifier.issuenumber | 1 |
| dc.format.medium | text |
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