Matches in SemOpenAlex for { <https://semopenalex.org/work/W3110846081> ?p ?o ?g. }
Showing items 1 to 77 of
77
with 100 items per page.
- W3110846081 abstract "Medical images form an essential source of information for various important processes such as diagnosis of diseases, surgical planning, medical reference, research and training. Therefore, effective and meaningful search and classification of these images are vital. Most of the medical image classification and retrieval systems use visual feature matching technique; that is extracting low-level visual features of shape, color and texture from an image and matching these features with features in the database. However, there is a semantic gap which is a gap between a low-level feature and high-level concept, the way humans interpret an image. Manual annotation is often used for medical domain image database system; that is a user enters some descriptive keywords about the image and this description is stored as metadata. However, manual annotation has problems and limitations such as domain knowledge needed by an annotator, cost incurred to annotate large amount of images, time consuming and inconsistency whereby different annotators or domain experts might use different keywords. The process by which a computer system automatically assigns keywords or concepts to an image is referred to as automatic image annotation which can provide a platform to bridge the semantic gap. Image annotation can be considered as classification problem. In addition, machine learning techniques could be used for classification. This implies that training data can be used to learn or build a classifier; and subsequently this classifier can be used to classify or annotate test images.The main contribution in this research work is the modeling and development of framework of classifiers for multi-level automatic image annotation. The proposed framework evolves on the idea that multi-level feature extraction and concept hierarchy can improve content description of an image. In addition image retrieval is based on either text or image content. A system code-named “Medical Image Annotation and Retrieval System” (MIARS) was implemented based on this framework. The novel method of image indexing using multi-level features is also incorporated in MIARS. Experiment performance measures were conducted to evaluate the novel implementation of multilevel automatic medical image annotation framework and machine learning techniques." @default.
- W3110846081 created "2020-12-21" @default.
- W3110846081 creator A5070132115 @default.
- W3110846081 date "2009-01-01" @default.
- W3110846081 modified "2023-09-27" @default.
- W3110846081 title "Multilevel Automatic Medical Image Annotation" @default.
- W3110846081 hasPublicationYear "2009" @default.
- W3110846081 type Work @default.
- W3110846081 sameAs 3110846081 @default.
- W3110846081 citedByCount "0" @default.
- W3110846081 crossrefType "journal-article" @default.
- W3110846081 hasAuthorship W3110846081A5070132115 @default.
- W3110846081 hasConcept C111919701 @default.
- W3110846081 hasConcept C115961682 @default.
- W3110846081 hasConcept C134306372 @default.
- W3110846081 hasConcept C138885662 @default.
- W3110846081 hasConcept C153180895 @default.
- W3110846081 hasConcept C154945302 @default.
- W3110846081 hasConcept C1667742 @default.
- W3110846081 hasConcept C199579030 @default.
- W3110846081 hasConcept C23123220 @default.
- W3110846081 hasConcept C2776321320 @default.
- W3110846081 hasConcept C2776401178 @default.
- W3110846081 hasConcept C33923547 @default.
- W3110846081 hasConcept C36503486 @default.
- W3110846081 hasConcept C41008148 @default.
- W3110846081 hasConcept C41895202 @default.
- W3110846081 hasConcept C75294576 @default.
- W3110846081 hasConcept C86034646 @default.
- W3110846081 hasConcept C93518851 @default.
- W3110846081 hasConcept C95623464 @default.
- W3110846081 hasConceptScore W3110846081C111919701 @default.
- W3110846081 hasConceptScore W3110846081C115961682 @default.
- W3110846081 hasConceptScore W3110846081C134306372 @default.
- W3110846081 hasConceptScore W3110846081C138885662 @default.
- W3110846081 hasConceptScore W3110846081C153180895 @default.
- W3110846081 hasConceptScore W3110846081C154945302 @default.
- W3110846081 hasConceptScore W3110846081C1667742 @default.
- W3110846081 hasConceptScore W3110846081C199579030 @default.
- W3110846081 hasConceptScore W3110846081C23123220 @default.
- W3110846081 hasConceptScore W3110846081C2776321320 @default.
- W3110846081 hasConceptScore W3110846081C2776401178 @default.
- W3110846081 hasConceptScore W3110846081C33923547 @default.
- W3110846081 hasConceptScore W3110846081C36503486 @default.
- W3110846081 hasConceptScore W3110846081C41008148 @default.
- W3110846081 hasConceptScore W3110846081C41895202 @default.
- W3110846081 hasConceptScore W3110846081C75294576 @default.
- W3110846081 hasConceptScore W3110846081C86034646 @default.
- W3110846081 hasConceptScore W3110846081C93518851 @default.
- W3110846081 hasConceptScore W3110846081C95623464 @default.
- W3110846081 hasLocation W31108460811 @default.
- W3110846081 hasOpenAccess W3110846081 @default.
- W3110846081 hasPrimaryLocation W31108460811 @default.
- W3110846081 hasRelatedWork W110413022 @default.
- W3110846081 hasRelatedWork W1964468475 @default.
- W3110846081 hasRelatedWork W1996283195 @default.
- W3110846081 hasRelatedWork W2025660389 @default.
- W3110846081 hasRelatedWork W2029215718 @default.
- W3110846081 hasRelatedWork W2046930979 @default.
- W3110846081 hasRelatedWork W2050113278 @default.
- W3110846081 hasRelatedWork W2052697133 @default.
- W3110846081 hasRelatedWork W2088466951 @default.
- W3110846081 hasRelatedWork W2107640175 @default.
- W3110846081 hasRelatedWork W2138454757 @default.
- W3110846081 hasRelatedWork W2169031860 @default.
- W3110846081 hasRelatedWork W2187360541 @default.
- W3110846081 hasRelatedWork W2242710484 @default.
- W3110846081 hasRelatedWork W2304981023 @default.
- W3110846081 hasRelatedWork W2538322377 @default.
- W3110846081 hasRelatedWork W2797493659 @default.
- W3110846081 hasRelatedWork W2809580219 @default.
- W3110846081 hasRelatedWork W2996867699 @default.
- W3110846081 hasRelatedWork W3177930984 @default.
- W3110846081 isParatext "false" @default.
- W3110846081 isRetracted "false" @default.
- W3110846081 magId "3110846081" @default.
- W3110846081 workType "article" @default.