Point detection in textured ultrasound images

被引:2
|
作者
Thon, Stine Hverven [1 ]
Austeng, Andreas [1 ]
Hansen, Roy Edgar [1 ,2 ]
机构
[1] Univ Oslo, Dept Informat, POB 1080, NO-0316 Oslo, Norway
[2] Norwegian Def Res Estab FFI, POB 25, NO-2027 Kjeller, Norway
关键词
Detection; Multilook; Point scatterer; Texture; Whitening; Ultrasound; MICROCALCIFICATIONS; SCATTERERS;
D O I
10.1016/j.ultras.2023.106968
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Detection of point scatterers in textured ultrasound images can be challenging. This paper investigates how four multilook methods can improve the detection. We analyze many images with known point scatterer locations and randomly textured backgrounds. The normalized matched filter (NMF) and multilook coherence factor (MLCF) methods are normalized methods that do not require any texture correction prior to detection analysis. They are especially propitious when optimal texture correction of the ultrasound images is difficult to obtain. The results show significant improvement in detection performance when the MLCF method is weighted with the prewhitened and texture corrected image. The method can be applied even when we do not have prior knowledge about the optimal prewhitening limits. The multilook methods NMF and NMF weighted (NMFW) are very favorable methods to apply on images where acoustic noise dominates the speckle background.
引用
收藏
页数:10
相关论文
共 50 条
  • [31] Robust Detection of Point Correspondences in Stereo Images
    Stojanovic, A.
    Unger, M.
    ACTA POLYTECHNICA, 2007, 47 (4-5) : 23 - 28
  • [32] Critical point detection in fluid flow images
    Ford, RM
    INTERNATIONAL CONFERENCE ON IMAGE PROCESSING - PROCEEDINGS, VOL II, 1997, : 700 - 703
  • [33] Point target detection of infrared images with eigentargets
    Liu, Ruiming
    Liu, Erqi
    Yang, Jie
    Zhang, Tianhao
    Cao, Yuan
    OPTICAL ENGINEERING, 2007, 46 (11)
  • [34] Creating a Deep Learning Classifier for the Detection of Soft Tissue Infections Using Point-of-Care Ultrasound Images
    Li, N.
    DiPlacido, N.
    Barnes, R.
    Shah, A.
    Smith, H.
    Verplancken, E.
    Stem, C.
    Moake, M.
    Oliva, C.
    Cummings, E.
    ANNALS OF EMERGENCY MEDICINE, 2022, 80 (04) : S147 - S147
  • [35] Towards an Optimal Interest Point Detector for Measurements in Ultrasound Images
    Zukal, Martin
    Benes, Radek
    Cika, Petr
    Riha, Kamil
    MEASUREMENT SCIENCE REVIEW, 2013, 13 (06): : 329 - 338
  • [36] Detection of textured areas in natural images using an indicator based on component counts
    Bergman, Ruth
    Nachlieli, Hila
    Ruckenstein, Gitit
    JOURNAL OF ELECTRONIC IMAGING, 2008, 17 (04)
  • [37] Robust Crack Defect Detection in Inhomogeneously Textured Surface of Near Infrared Images
    Chen, Haiyong
    Zhao, Huifang
    Han, Da
    Yan, Haowei
    Zhang, Xiaofang
    Liu, Kun
    PATTERN RECOGNITION AND COMPUTER VISION (PRCV 2018), PT I, 2018, 11256 : 511 - 523
  • [38] Object CFAR detection in gamma-distributed textured-background images
    Alberola-López, C
    Casar-Corredera, JR
    de Miguel-Vela, G
    IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING, 1999, 146 (03): : 130 - 136
  • [39] Deep Autoencoders for Anomaly Detection in Textured Images Using CW-SSIM
    Bionda, Andrea
    Frittoli, Luca
    Boracchi, Giacomo
    IMAGE ANALYSIS AND PROCESSING, ICIAP 2022, PT II, 2022, 13232 : 669 - 680
  • [40] Object CFAR detection in gamma-distributed textured-background images
    ETSI Telecomunicacion, Valladolid, Spain
    IEE Proc Vision Image Signal Proc, 3 (130-136):