Smart cloud system with image processing server in diagnosing brain diseases dedicated for hospitals with limited resources.

The use of medical imaging in diagnosing brain disease is growing. The challenges are related to the big size of data and complexity of the image processing. High standard of hardware and software are demanded, which can only be provided in big hospitals. Our purpose was to provide a smart cloud sys...

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Publicado en:Technology & Health Care Vol. 25; no. 3; pp. 607 - 611
Autores principales: Fahmi, Fahmi, Nasution, Tigor H., Anggreiny, Anggreiny, Anggreiny
Formato: Journal Article
Publicado: Sage Publications Inc. 2017
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Smart cloud system with image processing server in diagnosing brain diseases dedicated for hospitals with limited resources.
      aug:
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          Fahmi, Fahmi
          Nasution, Tigor H.
          Anggreiny
          Anggreiny, Anggreiny
        affil: Department of Electrical Engineering, University of Sumatera Utara (USU), Medan, Indonesia.
      sug:
        subj:
          Brain Diseases
          Image Processing, Computer Assisted Methods
          Brain Neoplasms Diagnosis
          Equipment and Supplies
          Neuroradiography Methods
          Brain Neoplasms
          Brain Diseases Diagnosis
      ab: The use of medical imaging in diagnosing brain disease is growing. The challenges are related to the big size of data and complexity of the image processing. High standard of hardware and software are demanded, which can only be provided in big hospitals. Our purpose was to provide a smart cloud system to help diagnosing brain diseases for hospital with limited infrastructure. The expertise of neurologists was first implanted in cloud server to conduct an automatic diagnosis in real time using image processing technique developed based on ITK library and web service. Users upload images through website and the result, in this case the size of tumor was sent back immediately. A specific image compression technique was developed for this purpose. The smart cloud system was able to measure the area and location of tumors, with average size of 19.91 ± 2.38 cm2 and an average response time 7.0 ± 0.3 s. The capability of the server decreased when multiple clients accessed the system simultaneously: 14 ± 0 s (5 parallel clients) and 27 ± 0.2 s (10 parallel clients). The cloud system was successfully developed to process and analyze medical images for diagnosing brain diseases in this case for tumor.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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