Cloud Computing SaaS Paradigm for Efficient Modelling of Solar Features and Activities

Hayajneh, Sofyan

doi:10.4018/ijcac.2015070102

Cited by 2 publications

(2 citation statements)

References 45 publications

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“…bit-split slicing) along with other simple refinement, detection and classification techniques rather than complex ones of high computational cost. Also, further visualization and representation can be made making use of the state of the art utilization of cloud-based services (Hayajneh 2015).…”

Section: Discussionmentioning

confidence: 99%

High Quality - Low Computational Cost Technique for Automated Principal Object Segmentation Applied in Solar and Medical Imaging

Hayajneh¹,

Rashad²,

Saraereh³

et al. 2016

CIS

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The objective of this paper is to introduce a fully computerized, simple and low-computational cost technique that can be used in the preprocessing stages of digital images. This technique is specially designed to detect the principal (largest) closed shape object that embody the useful information in certain image types and neglect and avoid other noisy objects and artifacts. The detection process starts by calculating certain statistics of the image to estimate the amount of bit-plane slicing required to exclude the non-informative and noisy background. A simple closing morphological operation is then applied and followed by circular filter applied only on the outer coarse edge to finalize the detection process. The proposed technique takes its importance from the huge explosion of images that need accurate processing in real time speedy manner. The proposed technique is implemented using MATLAB and tested on many solar and medical images; it was shown by the quantitative evaluation that the proposed technique can handle real-life (e.g. solar, medical fundus) images and shows very good potential even under noisy and artifacts conditions. Compared to the publicly available datasets, 97% and 99% of similarity detection is achieved in medical and solar images, respectively. Although it is well-know, the morphological bit-plane slicing technique is hoped to be used in the preprocessing stages of different applications to ease the subsequent image processing stages especially in real time applications where the proposed technique showed dramatic (~100 times) saving in processing time.

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Section: Discussionmentioning

confidence: 99%

High Quality - Low Computational Cost Technique for Automated Principal Object Segmentation Applied in Solar and Medical Imaging

Hayajneh¹,

Rashad²,

Saraereh³

et al. 2016

CIS

View full text Add to dashboard Cite

show abstract

“…As future work, it is hoped to enhance the refinement stage by increasing the accuracy of separation of clustered nuclei so that overlapped region is associated more accurately and more meaningfully to the separated nuclei. From the other hand, it is of the future planes to provide such system as a software as a service (SaaS) [44] and to allow the integration of this system with other related systems.…”

Section: Conclusion and Further Workmentioning

confidence: 99%

Cascades Neural Network based Segmentation of Fluorescence Microscopy Cell Nuclei

Hayajneh¹,

Alomari²,

Al-Shargabi³

2018

ijacsa

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Abstract-The visual extraction of cellular, nuclear and tissue components from medical images is very vital in the diagnosis routine of different health related abnormalities and diseases. The objective of this work is to modify and efficiently combine different image processing methods supported by cascaded artificial neural networks in an automated system to perform segmentation analysis of medical microscopy images to extract nuclei located in either simple or complex clusters. The proposed system is applied on a publicly available data sets of microscopy nuclei cells. A GUI is designed and presented in this work to ease the analysis and screening of these images. The proposed system shows promising performance and reduced computational time cost. It is hoped that thus system and the corresponding GUI will construct platform base for several biomedical studies in the field of cellular imaging where further complex investigations and modelling of microscopy images could take place.

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Cloud Computing SaaS Paradigm for Efficient Modelling of Solar Features and Activities

Cited by 2 publications

References 45 publications

High Quality - Low Computational Cost Technique for Automated Principal Object Segmentation Applied in Solar and Medical Imaging

High Quality - Low Computational Cost Technique for Automated Principal Object Segmentation Applied in Solar and Medical Imaging

Cascades Neural Network based Segmentation of Fluorescence Microscopy Cell Nuclei

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