MIRACLE's Naive Approach to Medical Images Annotation
نویسندگان
چکیده
One of the proposed tasks of the ImageCLEF 2005 campaign has been an Automatic Annotation Task. The objective is to provide the classification of a given set of 1,000 previously unseen medical (radiological) images according to 57 predefined categories covering different medical pathologies. 9,000 classified training images are given which can be used in any way to train a classifier. The Automatic Annotation task uses no textual information, but image-content information only. This paper describes our participation in the automatic annotation task of ImageCLEF 2005.
منابع مشابه
A CAD System Framework for the Automatic Diagnosis and Annotation of Histological and Bone Marrow Images
Due to ever increasing of medical images data in the world’s medical centers and recent developments in hardware and technology of medical imaging, necessity of medical data software analysis is needed. Equipping medical science with intelligent tools in diagnosis and treatment of illnesses has resulted in reduction of physicians’ errors and physical and financial damages. In this article we pr...
متن کاملScalable Image Annotation by Summarizing Training Samples into Labeled Prototypes
By increasing the number of images, it is essential to provide fast search methods and intelligent filtering of images. To handle images in large datasets, some relevant tags are assigned to each image to for describing its content. Automatic Image Annotation (AIA) aims to automatically assign a group of keywords to an image based on visual content of the image. AIA frameworks have two main sta...
متن کاملFuzzy Neighbor Voting for Automatic Image Annotation
With quick development of digital images and the availability of imaging tools, massive amounts of images are created. Therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. Automatic image annotation (AIA) or refers to attaching words, keywords or comments to an image or to a selected part of it. In this paper,...
متن کاملConcept Propagation Based on Visual Similarity Application to Medical Image Annotation
This paper presents an approach for image annotation propagation to images which have no annotations. In some specific domains, the assumption that visual similarity implies (partial) semantic similarity can be made. For instance, in medical imaging, two images of the same anatomic part in a given modality have a very similar appearance. In the proposed approach, a conceptual indexing phase ext...
متن کاملAutomatic Image Annotation Using a Semi-supervised Ensemble of Classifiers
Automatic image annotation consists on automatically labeling images, or image regions, with a pre-defined set of keywords, which are regarded as descriptors of the high-level semantics of the image. In supervised learning, a set of previously annotated images is required to train a classifier. Annotating a large quantity of images by hand is a tedious and time consuming process; so an alternat...
متن کامل