Comparing line detection methods for medical images

被引:0
|
作者
Zwiggelaar, R [1 ]
Parr, TC [1 ]
Taylor, CJ [1 ]
机构
[1] Univ Manchester, Dept Med Biophys, Wolfson Image Anal Unit, Manchester M13 9PT, Lancs, England
关键词
line detectors; medical images; orientation; line strength; structure;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
In medical image analysis there are various examples where the detection of linear structures can provide important information. These include mammography, blood vessel detection and the extraction of trebecular structure from bone images. There are several generic techniques which can be used to obtain linear structure information at a pixel level. Several of these techniques are compared on the basis of their preformance in detecting line strength and orientation. In addition we comment on the possibility of using the same techniques in a multi-scale approach to also obtain line scale information. The methods discussed include those based on simple orientation bins, a multidirectional line operator, directional second order Gaussian derivatives, directional morphology, curvilinear structures detection and directional Fourier space.
引用
收藏
页码:1161 / 1162
页数:2
相关论文
共 50 条
  • [1] Line detection methods for spectrogram images
    Lampert, Thomas A.
    O’Keefe, Simon E. M.
    Pears, Nick E.
    Advances in Intelligent and Soft Computing, 2009, 57 : 127 - 134
  • [2] Comparing different filtering and enhancement methods to evaluate the impact on the geometry reconstruction for medical images
    Joao, A. J.
    Gambaruto, A. M.
    Sequeira, A.
    COMPUTATIONAL VISION AND MEDICAL IMAGE PROCESSING: VIPIMAGE 2011, 2012, : 179 - 181
  • [3] Comparing methods to denoise mammographic images
    Mayo, P
    Rodenas, F
    Verdú, G
    PROCEEDINGS OF THE 26TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7, 2004, 26 : 247 - 250
  • [4] Compression methods for medical images
    Uchiyama, Akihiko
    Jamzad, Mansour
    Memoirs of the School of Science and Engineering, Waseda University, 1988, (52): : 29 - 43
  • [5] Comparing Images for Document Plagiarism Detection
    Iwanowski, Marcin
    Cacko, Arkadiusz
    Sarwas, Grzegorz
    COMPUTER VISION AND GRAPHICS, ICCVG 2016, 2016, 9972 : 532 - 543
  • [6] Methods for Medical Images Contrast Measuring and Enhancement to Improve the Accuracy of Pathology Detection
    Kutsenko, Alexander
    Megel, Yury
    Kovalenko, Sergii
    Kovalenko, Svitlana
    Pelikh, Daniil
    Rybalka, Antonina
    2022 XXXII INTERNATIONAL SCIENTIFIC SYMPOSIUM METROLOGY AND METROLOGY ASSURANCE (MMA), 2022, : 138 - 143
  • [7] Line Detection in Range Images
    Xu, Cun Lu
    Lei, Qin
    Guo, Zhi Cheng
    2009 5TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-8, 2009, : 1915 - +
  • [8] Comparing Image Similarity Methods for Face Images
    Ornek, Ahmet Haydar
    Celik, Mustafa
    Alper, Ozan Can
    INTERNATIONAL CONFERENCE ON ELECTRICAL, COMPUTER AND ENERGY TECHNOLOGIES (ICECET 2021), 2021, : 1581 - 1584
  • [9] On-line peak detection in medical time series with adaptive regression methods
    Grillenzoni, Carlo
    Fornaciari, Michele
    ECONOMETRICS AND STATISTICS, 2019, 10 : 134 - 150
  • [10] Methods for Medical Images Analyzing and Processing
    Obuhova, Natalia A.
    Motyko, Alexandr A.
    PROCEEDINGS OF THE 2017 IEEE RUSSIA SECTION YOUNG RESEARCHERS IN ELECTRICAL AND ELECTRONIC ENGINEERING CONFERENCE (2017 ELCONRUS), 2017, : 706 - 708