Medical Image Prediction Using Artificial Neural Networks

被引:1
|
作者
Xhako, Dafina [1 ]
Hyka, Niko [2 ]
机构
[1] Polytech Univ Tirana, Fac Math Engn & Phys Engn, Dept Phys Engn, Tirana, Albania
[2] Med Univ Tirana, Fac Med Tech Sci, Dept Diagnost, Tirana, Albania
关键词
medical images; neural networks; interpolation;
D O I
10.1063/1.5135451
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Artificial Neural Networks (ANN) have been applied to solve a large number of real-world problems, considerable complexity. Solving problems that are too complex for conventional technologies is the main advantage of ANN. In general, these problems include pattern recognition and forecasting. ANN have been used in the medical imaging, in computer aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration. In this paper we use ANN as a prediction method in medical images to complete the missing data in MRI and CT images. By using these methods, we can eliminate artifacts of image and visualize the new image which is much closer to the desired one. This image can be used for diagnostic purposes or radiotherapy.
引用
收藏
页数:4
相关论文
共 50 条
  • [21] Time series prediction using artificial neural networks
    Pérez-Chavarríia, MA
    Hidalgo-Silva, HH
    Ocampo-Torres, FJ
    CIENCIAS MARINAS, 2002, 28 (01) : 67 - 77
  • [22] Prediction of extrudate properties using artificial neural networks
    Shankar, T. J.
    Bandyopadhyay, S.
    FOOD AND BIOPRODUCTS PROCESSING, 2007, 85 (C1) : 29 - 33
  • [23] Prediction of groundwater drawdown using artificial neural networks
    Vahid Gholami
    Hossein Sahour
    Environmental Science and Pollution Research, 2022, 29 : 33544 - 33557
  • [24] Prediction of properties of rubber by using artificial neural networks
    Vijayabaskar, V
    Gupta, R
    Chakrabarti, PP
    Bhowmick, AK
    JOURNAL OF APPLIED POLYMER SCIENCE, 2006, 100 (03) : 2227 - 2237
  • [25] Lactose Intolerance Prediction Using Artificial Neural Networks
    Spahic, Lemana
    Sehovic, Emir
    Secerovic, Alem
    Dozic, Zerina
    Smajlovic-Skenderagic, Lejla
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING, CMBEBIH 2019, 2020, 73 : 505 - 510
  • [26] Prediction of tunnel convergence using Artificial Neural Networks
    Mahdevari, Satar
    Torabi, Seyed Rahman
    TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY, 2012, 28 : 218 - 228
  • [27] Prediction of Modal Shift Using Artificial Neural Networks
    Akgol, Kadir
    Aydin, Metin Mutlu
    Asilkan, Ozcan
    Gunay, Banihan
    TEM JOURNAL-TECHNOLOGY EDUCATION MANAGEMENT INFORMATICS, 2014, 3 (03): : 223 - 229
  • [28] Prediction of wheat yield using artificial neural networks
    Safa, B
    Khalili, A
    Teshnehlab, M
    Liaghat, AM
    15TH CONFERENCE ON BIOMETEOROLOGY AND AEROBIOLOGY JOINT WITH THE 16TH INTERNATIONAL CONGRESS ON BIOMETEOROLOGY, 2002, : 350 - 351
  • [29] Soil salinity prediction using artificial neural networks
    Patel, RM
    Prasher, SO
    Goel, PK
    Bassi, R
    JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, 2002, 38 (01): : 91 - 100
  • [30] Prediction of slump in concrete using artificial neural networks
    Agrawal, V.
    Sharma, A.
    World Academy of Science, Engineering and Technology, 2010, 69 : 25 - 32