Content-based Medical Image Retrieval for Liver CT Annotation
Journal Title: Transactions on Machine Learning and Artificial Intelligence - Year 2017, Vol 5, Issue 4
Abstract
The increase number of medical image stored and saved every day presents a unique opportunity for contentbased medical image retrieval (CBMIR) systems. In this paper, we propose contentbased medical image retrieval for annotating liver CT scans images in order to generate a structured report. For that, we have used the Bidimentional Empirical Mode Decomposition (BEMD), and then we have applied Gabor wavelet transform to extract the mean and the standard deviation as features descriptors. Finally, a proposed similarity distance was employed to retrieve the most similar training images to the image query, and a majority voting scheme was used to select the answers for an unannotated image. We have used the IMAGECLEF 2015 annotation dataset and the obtained score was 88.9%.
Authors and Affiliations
Imane Nedjar, Saïd Mahmoudi, Mohammed Amine Chikh
Keywords
Related Articles
- EP ID EP308474
- DOI 10.14738/tmlai.54.2985
- Views 69
- Downloads 0
Entrepreneur: Artificial Human Optimization
A new field titled ‘Artificial Human Optimization’ is introduced in this paper. All optimization methods which were proposed based on Artificial Humans will come under this new field. Less than 20 papers were published i...
Improved HMM for Cursive Arabic Handwriting Recognition System Using MLP Classifier
Recognizing unconstrained cursive Arabic handwritten text is a very challenging task the use of hybrid classification to take advantage of the strong modeling of Hidden Markov Models (HMM) and the large capacity of discr...
Using Machine Learning Algorithms for Cloud Client Prediction Models in a Web VM Resource Provisioning Environment
In order to meet Service Level Agreement (SLA) requirements, efficient scaling of Virtual Machine (VM) resources in cloud computing needs to be provisioned ahead due to the instantiation time required by the VM. One way...
Absorption Spectra Analysis using Modified Self-Organizing Feature Maps
This research demonstrates an application of a modified self-organizing feature map (SOFM) algorithm to analyze and discover the quality of chemical absorption spectrum data. By forming an NxN neural array from input fea...
Contextual Arabic Handwriting Recognition System Using Embedded Training Based Hybrid HMM/MLP Models
Recognizing unconstrained cursive Arabic handwritten text is a very challenging task the use of hybrid classification to take advantage of the strong modeling of Hidden Markov Models (HMM) and the large capacity of discr...