Extending UML for Conceptual Modeling of Annotation of Medical Images

07/03/2013
by   Mouhamed Gaith Ayadi, et al.
0

Imaging has occupied a huge role in the management of patients, whether hospitalized or not. Depending on the patients clinical problem, a variety of imaging modalities were available for use. This gave birth of the annotation of medical image process. The annotation is intended to image analysis and solve the problem of semantic gap. The reason for image annotation is due to increase in acquisition of images. Physicians and radiologists feel better while using annotation techniques for faster remedy in surgery and medicine due to the following reasons: giving details to the patients, searching the present and past records from the larger databases, and giving solutions to them in a faster and more accurate way. However, classical conceptual modeling does not incorporate the specificity of medical domain specially the annotation of medical image. The design phase is the most important activity in the successful building of annotation process. For this reason, we focus in this paper on presenting the conceptual modeling of the annotation of medical image by defining a new profile using the StarUML extensibility mechanism.

READ FULL TEXT

page 6

page 7

research
12/31/2013

Medical Image Fusion: A survey of the state of the art

Medical image fusion is the process of registering and combining multipl...
research
05/17/2013

Indexing Medical Images based on Collaborative Experts Reports

A patient is often willing to quickly get, from his physician, reliable ...
research
06/02/2013

Using a bag of Words for Automatic Medical Image Annotation with a Latent Semantic

We present in this paper a new approach for the automatic annotation of ...
research
11/26/2021

Modeling Human Preference and Stochastic Error for Medical Image Segmentation with Multiple Annotators

Manual annotation of medical images is highly subjective, leading to ine...
research
07/14/2020

Universal Model for Multi-Domain Medical Image Retrieval

Medical Image Retrieval (MIR) helps doctors quickly find similar patient...
research
10/29/2022

2D and 3D CT Radiomic Features Performance Comparison in Characterization of Gastric Cancer: A Multi-center Study

Objective: Radiomics, an emerging tool for medical image analysis, is po...
research
07/26/2019

Spatial Process Decomposition for Quantitative Imaging Biomarkers Using Multiple Images of Varying Shapes

Quantitative imaging biomarkers (QIB) are extracted from medical images ...

Please sign up or login with your details

Forgot password? Click here to reset