Designing an Automated System for Medical Diagnosis
Author: Parekh, Ranjan
Keywords: Medical Diagnosis
Medical Offices- Automation
Medical Image Analysis
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.
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.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 | 8p. |
dc.format.mimetype | application/pdf |
dc.language.iso | English |
dc.publisher | National Council of Science Museums, Kolkata |
dc.subject | Medical Diagnosis Medical Offices- Automation Medical Image Analysis |
dc.type | Article |
dc.identifier.issuenumber | Number I |
dc.identifier.volumenumber | Volume III |
dc.date.copyright | 2012 |
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.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 | 8p. |
dc.format.mimetype | application/pdf |
dc.language.iso | English |
dc.publisher | National Council of Science Museums, Kolkata |
dc.subject | Medical Diagnosis Medical Offices- Automation Medical Image Analysis |
dc.type | Article |
dc.identifier.issuenumber | Number I |
dc.identifier.volumenumber | Volume III |
dc.date.copyright | 2012 |
dc.format.medium | text |