The Business Process Management (BPM) as an advanced paradigm in workflow management has been very a very active research topic in the field software engineering and process management. The goal of this contribution is to take BPM advantages into the image processing -in particular medical image analysis- to provide a consistent and comprehensive software framework. A case study is also presented in this paper and the possibility for applying BPM on image analysis is specified separately. Furthermore, several quality attributes are addressed to create modifiable, reusable, and flexible framework for the medical imaging community. The present research is expected to draw attentions from medical image analysis to BPM, and make possible future enhancements in BPM’s application.
Published in | Computational Biology and Bioinformatics (Volume 3, Issue 3) |
DOI | 10.11648/j.cbb.20150303.11 |
Page(s) | 40-44 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
Business Process Management, Image Analysis, Software Engineering
[1] | Gonzales, R. C. and Woods, R. E. (2008). Digital Image Processing. Prentice Hall, USA. |
[2] | Shapiro, L. G. and Stockman, G. C. (2011). Computer Vision. Prentice Hall, USA. |
[3] | Van Der Aalst, W. M. P. (2003). Challenges in business process management: Verification of business processes using Petri nets. Bulletin of the EATCS, 80, 174-199. |
[4] | Rantanen, V., Valori, M., & Hautaniemi, S. (2014). Anima: modular workflow system for comprehensive image data analysis. Frontiers in bioengineering and biotechnology, 2. |
[5] | Weske, M. (2012). Business process management: concepts, languages, architectures. Springer Science & Business Media. |
[6] | Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2):91-110. |
[7] | Shotten, J., Fitzgibbon, A., Cook, M., Sharp, T., Finocchio, M, Moore, R., Kipman, A., and Blake, A. (2011). Real-time human pose recognition in parts from a single depth image. CVPR 2011. |
[8] | Tafti, A. P., Malakooti, M. V., Ashourian, M., and Janosepah, S. (2011). Digital image forgery detection through data embedding in spatial domain and cellular automata. In proceeding of the International Conference on Digital Content, Multimedia Technology and its Applications (IDCTA), pages 11-15. |
[9] | Tafti, A. P., Naji, H. R., and Malakooti, M. V. (2012). An efficient algorithm for human cell detection in electron microscope images based on cluster analysis and vector quantization techniques. In proceeding of the Second International Conference on Digital Information and Communication Technology and it's Applications (DICTAP), pages 125-129. |
[10] | Tafti, A. P., Rohani, F. Malakooti, M. V., and Moghaddasifar, M. A. (2012). RGB digital image forgery detection using Singular Value Decomposition and one dimensional Cellular Automata. In Proceeding of the International Conference on Computing Technology and Information Management (ICCM), pages 483-488. |
[11] | Rohani, F. Hassannia, H., Moghaddasifar, M. A., and Sagheb, E. (2014). Human cell detection in microscopic images through Discrete Cosine Transform and Gaussian Mixture Model. Computational Biology and Bioinformatics, 2(4): 52-56. |
[12] | Tafti, A. P., Kirkpatrick, A. B., Owen, H. A., and Z. Yu. (2014). 3D microscopy vision using multiple view geometry and differential evolutionary approaches. The 10th International Symposium on Visual Computing (ISVC), LNCS 8888, pages 141-152. |
[13] | Mišić, D., Mišić, M., MilanTrifunović, T. A., & Matić,(20124) P. AHP Based Comparison of open-source BPM Systems. |
[14] | Bardosi, Z., Granata, D., Lugos, G.., Tafti, A. P., Saxena, S. (2014). Metacarpal Bones Localization in X-ray Imagery Using Particle Filter Segmentation. arXiv preprint arXiv:1412.8197. |
[15] | Mousa, A. H., Shiratuddin, N., & Bakar, M. S. A. (2015). Process Oriented Data Virtualization Design Model for Business Processes Evaluation (PODVDM) Research in Progress. Jurnal Teknologi, 72(4). |
[16] | Bochon, I., Ivens, V., & Nagel, R. (2015). Challenges of cloud business process management. In Cloud Computing for Logistics (pp. 119-139). Springer International Publishing. |
[17] | Harmon, P. (2015). The scope and evolution of business process management. In Handbook on Business Process Management 1 (pp. 37-80). Springer Berlin Heidelberg. |
[18] | Anntonucci, I. L., & Goeke, R. J. (2009). Analysis of Business Process Management Skills and Characteristics. Widener University, May, 7. |
[19] | Van der Aalst, W. M., Reijers, H. A., Weijters, A. J., van Dongen, B. F., De Medeiros, A. A., Song, M., & Verbeek, H. M. W. (2007). Business process mining: An industrial application. Information Systems, 32(5), 713-732. |
[20] | Van der Aalst, W. M. (2007). Exploring the CSCW spectrum using process mining. Advanced Engineering Informatics, 21(2), 191-199. |
[21] | Van der Aalst, W. M. P. (2010). Challenges in business process mining. Applied Stochastic Models in Business and Industry (to appear). |
[22] | Malik, T. S. (2009). PROCESS MANAGEMENT: Practical Guidelines to Successful Implementation. Global India Publications. |
[23] | Dustdar, S., Fiadeiro, J. L., & Sheth, A. (Eds.). (2006). Business Process Management: 4th International Conference, BPM 2006, Vienna, Austria, September 5-7, 2006, Proceedings (Vol. 4102). Springer Science & Business Media. |
[24] | Zur Muehlen, M. (2004). Workflow-based process controlling: foundation, design, and application of workflow-driven process information systems (Vol. 6). Michael zur Muehlen. |
[25] | Tafti, A. P., Hassannia, H., Yu, Z. (2015). siftservice.com – Turning a Computer Vision Algorithm into a World Wide Web Service. arXiv preprint arXiv:1504.02840. |
APA Style
Faezeh Rohani, Mohammad Amin Moghaddasi Far, Fatemeh Fazayeli Bavojdan. (2015). From Business Process Management to Flexible Image Analysis Applications: A Case Study. Computational Biology and Bioinformatics, 3(3), 40-44. https://doi.org/10.11648/j.cbb.20150303.11
ACS Style
Faezeh Rohani; Mohammad Amin Moghaddasi Far; Fatemeh Fazayeli Bavojdan. From Business Process Management to Flexible Image Analysis Applications: A Case Study. Comput. Biol. Bioinform. 2015, 3(3), 40-44. doi: 10.11648/j.cbb.20150303.11
AMA Style
Faezeh Rohani, Mohammad Amin Moghaddasi Far, Fatemeh Fazayeli Bavojdan. From Business Process Management to Flexible Image Analysis Applications: A Case Study. Comput Biol Bioinform. 2015;3(3):40-44. doi: 10.11648/j.cbb.20150303.11
@article{10.11648/j.cbb.20150303.11, author = {Faezeh Rohani and Mohammad Amin Moghaddasi Far and Fatemeh Fazayeli Bavojdan}, title = {From Business Process Management to Flexible Image Analysis Applications: A Case Study}, journal = {Computational Biology and Bioinformatics}, volume = {3}, number = {3}, pages = {40-44}, doi = {10.11648/j.cbb.20150303.11}, url = {https://doi.org/10.11648/j.cbb.20150303.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cbb.20150303.11}, abstract = {The Business Process Management (BPM) as an advanced paradigm in workflow management has been very a very active research topic in the field software engineering and process management. The goal of this contribution is to take BPM advantages into the image processing -in particular medical image analysis- to provide a consistent and comprehensive software framework. A case study is also presented in this paper and the possibility for applying BPM on image analysis is specified separately. Furthermore, several quality attributes are addressed to create modifiable, reusable, and flexible framework for the medical imaging community. The present research is expected to draw attentions from medical image analysis to BPM, and make possible future enhancements in BPM’s application.}, year = {2015} }
TY - JOUR T1 - From Business Process Management to Flexible Image Analysis Applications: A Case Study AU - Faezeh Rohani AU - Mohammad Amin Moghaddasi Far AU - Fatemeh Fazayeli Bavojdan Y1 - 2015/05/26 PY - 2015 N1 - https://doi.org/10.11648/j.cbb.20150303.11 DO - 10.11648/j.cbb.20150303.11 T2 - Computational Biology and Bioinformatics JF - Computational Biology and Bioinformatics JO - Computational Biology and Bioinformatics SP - 40 EP - 44 PB - Science Publishing Group SN - 2330-8281 UR - https://doi.org/10.11648/j.cbb.20150303.11 AB - The Business Process Management (BPM) as an advanced paradigm in workflow management has been very a very active research topic in the field software engineering and process management. The goal of this contribution is to take BPM advantages into the image processing -in particular medical image analysis- to provide a consistent and comprehensive software framework. A case study is also presented in this paper and the possibility for applying BPM on image analysis is specified separately. Furthermore, several quality attributes are addressed to create modifiable, reusable, and flexible framework for the medical imaging community. The present research is expected to draw attentions from medical image analysis to BPM, and make possible future enhancements in BPM’s application. VL - 3 IS - 3 ER -