Super-resolution Reconstruction for Tongue MR Images

被引:2
|
作者
Woo, Jonghye [1 ,2 ]
Bai, Ying [3 ]
Roy, Snehashis [2 ]
Murano, Emi Z. [2 ]
Stone, Maureen [1 ]
Prince, Jerry L. [2 ]
机构
[1] Univ Maryland, Baltimore, MD 21201 USA
[2] Johns Hopkins Univ, Baltimore, MD 21218 USA
[3] HeartFlow Inc, Redwood City, CA 94063 USA
来源
关键词
VOLUME RECONSTRUCTION; INTERNAL TONGUE; FETAL;
D O I
10.1117/12.911445
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Magnetic resonance (MR) images of the tongue have been used in both clinical medicine and scientific research to reveal tongue structure and motion. In order to see different features of the tongue and its relation to the vocal tract it is beneficial to acquire three orthogonal image stacks-e. g., axial, sagittal and coronal volumes. In order to maintain both low noise and high visual detail, each set of images is typically acquired with in-plane resolution that is much better than the through-plane resolution. As a result, any one data set, by itself, is not ideal for automatic volumetric analyses such as segmentation and registration or even for visualization when oblique slices are required. This paper presents a method of super-resolution reconstruction of the tongue that generates an isotropic image volume using the three orthogonal image stacks. The method uses preprocessing steps that include intensity matching and registration and a data combination approach carried out by Markov random field optimization. The performance of the proposed method was demonstrated on five clinical datasets, yielding superior results when compared with conventional reconstruction methods.
引用
收藏
页数:8
相关论文
共 50 条
  • [31] Super-resolution and reconstruction of sparse sub-wavelength images
    Gazit, Snir
    Szameit, Alexander
    Eldar, Yonina C.
    Segev, Mordechai
    OPTICS EXPRESS, 2009, 17 (26): : 23920 - 23946
  • [32] Super-Resolution Reconstruction Algorithm To MODIS Remote Sensing Images
    Shen, Huanfeng
    Ng, Michael K.
    Li, Pingxiang
    Zhang, Liangpei
    COMPUTER JOURNAL, 2009, 52 (01): : 90 - 100
  • [33] SUPER-RESOLUTION RECONSTRUCTION OF UAV IMAGES FOR MAIZE TASSEL DETECTION
    Yu, Lei
    Zhu, Deli
    Xu, Zhao
    Fu, Haibin
    JOURNAL OF THE ASABE, 2025, 68 (01): : 1 - 12
  • [34] Regularized super-resolution reconstruction of images using wavelet fusion
    El-Khamy, SE
    Hadhoud, MM
    Dessouky, MI
    Salam, BM
    El-Samie, FEA
    OPTICAL ENGINEERING, 2005, 44 (09)
  • [35] Super-resolution and reconstruction of sparse images carried by incoherent light
    Shechtman, Yoav
    Gazit, Snir
    Szameit, Alexander
    Eldar, Yonina C.
    Segev, Mordechai
    OPTICS LETTERS, 2010, 35 (08) : 1148 - 1150
  • [36] Image Restoration Techniques in Super-Resolution Reconstruction of MRI images
    Alsayem, Hisham A.
    Kadah, Yasser M.
    2016 33RD NATIONAL RADIO SCIENCE CONFERENCE (NRSC), 2016, : 188 - 194
  • [37] Research on Super-Resolution Reconstruction Algorithm of Cultural Relic Images
    Liu J.
    Ge Y.-F.
    Tian M.
    Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2023, 51 (01): : 139 - 145
  • [38] DRUSR:Effect-Oriented Super-Resolution Reconstruction of Images
    Li, Hao
    Zhao, Guangzhe
    Computer Engineering and Applications, 2023, 59 (24): : 165 - 175
  • [39] Super-resolution reconstruction using insufficient number of low-resolution images
    Misaizu, Hiroyuki
    Inamura, Minoru
    IMETI 2008: INTERNATIONAL MULTI-CONFERENCE ON ENGINEERING AND TECHNOLOGICAL INNOVATION, VOL II, PROCEEDINGS, 2008, : 261 - +
  • [40] Gaussian Processes for Slice-Based Super-Resolution MR Images
    Vargas Cardona, Hernan Dario
    Lopez-Lopera, Andres F.
    Orozco, Alvaro A.
    Alvarez, Mauricio A.
    Hernandez Tamames, Juan Antonio
    Malpica, Norberto
    ADVANCES IN VISUAL COMPUTING, PT II (ISVC 2015), 2015, 9475 : 692 - 701