Sarina Mansor

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Enormous amounts of sequential medical images are produced in modern medical examinations, typically in Fluoroscopy. Although highly effective, such large quantities of images incur a high cost in terms of storage, processing time and transmission. This paper proposes a method for lossless compression of targeted parts within Fluoroscopy images, extracting(More)
In this paper, we represent a new framework that performs automated local wall motion analysis based on the combined information derived from a rest and stress sequence (a full stress echocardiography study). Since cardiac data inherits time-varying and sequential properties, we introduce a Hidden Markov Model (HMM) approach to classify stress(More)
Content Based Image Retrieval (CBIR) has been an active and fast growing research area in both image processing and data mining. Malaysia has been recognized with a rich marine ecosystem. Challenges of these images are low resolution, translation, and transformation invariant. In this paper, we have designed an automated CBIR system to characterize the(More)
The massive number of medical images produced by fluoroscopic and other conventional diagnostic imaging devices demand a considerable amount of space for data storage. This paper proposes an effective method for lossless compression of fluoroscopic images. The main contribution in this paper is the extraction of the regions of interest (ROI) in fluoroscopic(More)
Research on Content Based Image Retrieval (CBIR) has become popular as it offers solutions to overcome or complement the drawbacks of Text Based Image Retrieval (TBIR). In CBIR, feature extraction and feature matching are two critical processes, which are of high importance to the retrieval performance of the system. This paper introduces a new approach to(More)
Systematic procedures for data storage and retrieval are obligatory to the fluoroscopy and other conventional diagnostic imaging devices in which they produce a large number of medical images. This paper proposes and efficient method for lossless compression of fluoroscopic images. There are two components in this paper; segmentation and compression. For(More)
Keywords: Fluoroscopy medical images-Lossless image compression-Diagnostically lossless compression-Run-Length Encoding-Huffman Coding-Correlation. Diagnostic imaging devices such as fluoroscopy produce a vast number of sequential images, ranging from localization images to functional tracking of the contrast agent moving through anatomical structures such(More)
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