Automatic Classification and Retrieval of Brain Hemorrhages


Ahmad Fauzi, Mohammad Faizal and Haw, Su Cheng and Ng, Hu and Yap, Timothy Tzen Vun and Tong, Hau Lee (2019) Automatic Classification and Retrieval of Brain Hemorrhages. In: Computational Science and Technology. Automatic Classification and Retrieval of Brain Hemorrhages, 481 . Springer, Lecture Notes in Electrical Engineering, pp. 1-11. ISBN 978-981-13-2622-6

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In this work, Computed Tomography (CT) brain images are adopted for the annotation of different types of hemorrhages. The ultimate objective is to devise the semantics-based retrieval system for retrieving the images based on the different keywords. The adopted keywords are hemorrhagic slices, intraaxial, subdural and extradural slices. The proposed approach is consisted of three separated annotation processes are proposed which are annotation of hemorrhagic slices, annotation of intra-axial and annotation of subdural and extradural. The dataset with 519 CT images is obtained from two collaborating hospitals. For the classification, support vector machine (SVM) with radial basis function (RBF) kernel is considered. On overall, the classification results from each experiment achieved precision and recall of more than 79%. After the classification, the images will be annotated with the classified keywords together with the obtained decision values. During the retrieval, the relevant images will be retrieved and ranked correspondingly according to the decision values.

Item Type: Book Section
Uncontrolled Keywords: Image Classification
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Divisions: Faculty of Computing and Informatics (FCI)
Faculty of Engineering (FOE)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 23 Sep 2021 02:17
Last Modified: 23 Sep 2021 02:17


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