Literature DB >> 23286163

Co-segmentation of functional and anatomical images.

Ulas Bagci1, Jayaram K Udupa, Jianhua Yao, Daniel J Mollura.   

Abstract

This paper presents a novel method for segmenting functional and anatomical structures simultaneously. The proposed method unifies domains of anatomical and functional images (PET-CT), represents them in a product lattice, and performs simultaneous delineation of regions based on a random walk image segmentation. In addition, we propose a simple yet efficient object/background seed localization method, where background and foreground object cues are automatically obtained from PET images and propagated onto the corresponding anatomical images (CT). In our experiments, abnormal anatomies on PET-CT images from human subjects are segmented synergistically by the proposed fully automatic co-segmentation method with high precision (mean DSC of 91.44%) in seconds (avg. 40 seconds).

Entities:  

Keywords:  Joint Segmentation; Object Detection; PET-CT; Random Walk

Mesh:

Year:  2012        PMID: 23286163      PMCID: PMC3539250          DOI: 10.1007/978-3-642-33454-2_57

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  5 in total

1.  Segmentation of PET volumes by iterative image thresholding.

Authors:  Walter Jentzen; Lutz Freudenberg; Ernst G Eising; Melanie Heinze; Wolfgang Brandau; Andreas Bockisch
Journal:  J Nucl Med       Date:  2007-01       Impact factor: 10.057

2.  Random walks for image segmentation.

Authors:  Leo Grady
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2006-11       Impact factor: 6.226

3.  Simultaneous PET-MRI: a new approach for functional and morphological imaging.

Authors:  Martin S Judenhofer; Hans F Wehrl; Danny F Newport; Ciprian Catana; Stefan B Siegel; Markus Becker; Axel Thielscher; Manfred Kneilling; Matthias P Lichy; Martin Eichner; Karin Klingel; Gerald Reischl; Stefan Widmaier; Martin Röcken; Robert E Nutt; Hans-Jürgen Machulla; Kamil Uludag; Simon R Cherry; Claus D Claussen; Bernd J Pichler
Journal:  Nat Med       Date:  2008-03-23       Impact factor: 53.440

4.  Globally optimal tumor segmentation in PET-CT images: a graph-based co-segmentation method.

Authors:  Dongfeng Han; John Bayouth; Qi Song; Aakant Taurani; Milan Sonka; John Buatti; Xiaodong Wu
Journal:  Inf Process Med Imaging       Date:  2011

5.  Fully automated segmentation of oncological PET volumes using a combined multiscale and statistical model.

Authors:  David W G Montgomery; Abbes Amira; Habib Zaidi
Journal:  Med Phys       Date:  2007-02       Impact factor: 4.071

  5 in total
  16 in total

1.  Simultaneous cosegmentation of tumors in PET-CT images using deep fully convolutional networks.

Authors:  Zisha Zhong; Yusung Kim; Kristin Plichta; Bryan G Allen; Leixin Zhou; John Buatti; Xiaodong Wu
Journal:  Med Phys       Date:  2019-01-04       Impact factor: 4.071

Review 2.  A review on segmentation of positron emission tomography images.

Authors:  Brent Foster; Ulas Bagci; Awais Mansoor; Ziyue Xu; Daniel J Mollura
Journal:  Comput Biol Med       Date:  2014-04-28       Impact factor: 4.589

3.  In vivo prediction of tuberculosis-associated cavity formation in rabbits.

Authors:  Brian Luna; André Kubler; Christer Larsson; Brent Foster; Ulas Bagci; Daniel J Mollura; Sanjay K Jain; William R Bishai
Journal:  J Infect Dis       Date:  2014-08-12       Impact factor: 5.226

4.  Joint segmentation of anatomical and functional images: applications in quantification of lesions from PET, PET-CT, MRI-PET, and MRI-PET-CT images.

Authors:  Ulas Bagci; Jayaram K Udupa; Neil Mendhiratta; Brent Foster; Ziyue Xu; Jianhua Yao; Xinjian Chen; Daniel J Mollura
Journal:  Med Image Anal       Date:  2013-05-23       Impact factor: 8.545

5.  A Novel Framework for Automated Segmentation and Labeling of Homogeneous Versus Heterogeneous Lung Tumors in [18F]FDG-PET Imaging.

Authors:  Motahare Soufi; Alireza Kamali-Asl; Parham Geramifar; Arman Rahmim
Journal:  Mol Imaging Biol       Date:  2017-06       Impact factor: 3.488

6.  Tumor co-segmentation in PET/CT using multi-modality fully convolutional neural network.

Authors:  Xiangming Zhao; Laquan Li; Wei Lu; Shan Tan
Journal:  Phys Med Biol       Date:  2018-12-21       Impact factor: 3.609

7.  A hybrid method for airway segmentation and automated measurement of bronchial wall thickness on CT.

Authors:  Ziyue Xu; Ulas Bagci; Brent Foster; Awais Mansoor; Jayaram K Udupa; Daniel J Mollura
Journal:  Med Image Anal       Date:  2015-05-14       Impact factor: 8.545

8.  Segmentation of PET images for computer-aided functional quantification of tuberculosis in small animal models.

Authors:  Brent Foster; Ulas Bagci; Bappaditya Dey; Brian Luna; William Bishai; Sanjay Jain; Daniel J Mollura
Journal:  IEEE Trans Biomed Eng       Date:  2013-11-05       Impact factor: 4.538

9.  Optimal co-segmentation of tumor in PET-CT images with context information.

Authors:  Qi Song; Junjie Bai; Dongfeng Han; Sudershan Bhatia; Wenqing Sun; William Rockey; John E Bayouth; John M Buatti; Xiaodong Wu
Journal:  IEEE Trans Med Imaging       Date:  2013-05-16       Impact factor: 10.048

10.  3D Alpha Matting Based Co-segmentation of Tumors on PET-CT Images.

Authors:  Zisha Zhong; Yusung Kim; John Buatti; Xiaodong Wu
Journal:  Mol Imaging Reconstr Anal Mov Body Organs Stroke Imaging Treat (2017)       Date:  2017-09-09
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