Literature DB >> 19119055

Simulation of brain tumors in MR images for evaluation of segmentation efficacy.

Marcel Prastawa1, Elizabeth Bullitt, Guido Gerig.   

Abstract

Obtaining validation data and comparison metrics for segmentation of magnetic resonance images (MRI) are difficult tasks due to the lack of reliable ground truth. This problem is even more evident for images presenting pathology, which can both alter tissue appearance through infiltration and cause geometric distortions. Systems for generating synthetic images with user-defined degradation by noise and intensity inhomogeneity offer the possibility for testing and comparison of segmentation methods. Such systems do not yet offer simulation of sufficiently realistic looking pathology. This paper presents a system that combines physical and statistical modeling to generate synthetic multi-modal 3D brain MRI with tumor and edema, along with the underlying anatomical ground truth, Main emphasis is placed on simulation of the major effects known for tumor MRI, such as contrast enhancement, local distortion of healthy tissue, infiltrating edema adjacent to tumors, destruction and deformation of fiber tracts, and multi-modal MRI contrast of healthy tissue and pathology. The new method synthesizes pathology in multi-modal MRI and diffusion tensor imaging (DTI) by simulating mass effect, warping and destruction of white matter fibers, and infiltration of brain tissues by tumor cells. We generate synthetic contrast enhanced MR images by simulating the accumulation of contrast agent within the brain. The appearance of the the brain tissue and tumor in MRI is simulated by synthesizing texture images from real MR images. The proposed method is able to generate synthetic ground truth and synthesized MR images with tumor and edema that exhibit comparable segmentation challenges to real tumor MRI. Such image data sets will find use in segmentation reliability studies, comparison and validation of different segmentation methods, training and teaching, or even in evaluating standards for tumor size like the RECIST criteria (response evaluation criteria in solid tumors).

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Mesh:

Year:  2008        PMID: 19119055      PMCID: PMC2660387          DOI: 10.1016/j.media.2008.11.002

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  24 in total

1.  Spatial transformations of diffusion tensor magnetic resonance images.

Authors:  D C Alexander; C Pierpaoli; P J Basser; J C Gee
Journal:  IEEE Trans Med Imaging       Date:  2001-11       Impact factor: 10.048

2.  Registration of 3-D intraoperative MR images of the brain using a finite-element biomechanical model.

Authors:  M Ferrant; A Nabavi; B Macq; F A Jolesz; R Kikinis; S K Warfield
Journal:  IEEE Trans Med Imaging       Date:  2001-12       Impact factor: 10.048

3.  Model-Updated Image-Guided Neurosurgery Using the Finite Element Method: Incorporation of the Falx Cerebri.

Authors:  Michael I Miga; Keith D Paulsen; Francis E Kennedy; Alex Hartov; David W Roberts
Journal:  Med Image Comput Comput Assist Interv       Date:  1999-09

4.  Automatic segmentation of MR images of the developing newborn brain.

Authors:  Marcel Prastawa; John H Gilmore; Weili Lin; Guido Gerig
Journal:  Med Image Anal       Date:  2005-10       Impact factor: 8.545

5.  Twenty new digital brain phantoms for creation of validation image data bases.

Authors:  Berengère Aubert-Broche; Mark Griffin; G Bruce Pike; Alan C Evans; D Louis Collins
Journal:  IEEE Trans Med Imaging       Date:  2006-11       Impact factor: 10.048

6.  Fast and simple calculus on tensors in the log-Euclidean framework.

Authors:  Vincent Arsigny; Pierre Fillard; Xavier Pennec; Nicholas Ayache
Journal:  Med Image Comput Comput Assist Interv       Date:  2005

7.  Multimodality image registration by maximization of mutual information.

Authors:  F Maes; A Collignon; D Vandermeulen; G Marchal; P Suetens
Journal:  IEEE Trans Med Imaging       Date:  1997-04       Impact factor: 10.048

8.  Finite element modeling of brain tumor mass-effect from 3D medical images.

Authors:  Ashraf Mohamed; Christos Davatzikos
Journal:  Med Image Comput Comput Assist Interv       Date:  2005

9.  A brain tumor segmentation framework based on outlier detection.

Authors:  Marcel Prastawa; Elizabeth Bullitt; Sean Ho; Guido Gerig
Journal:  Med Image Anal       Date:  2004-09       Impact factor: 8.545

10.  Peritumoral diffusion tensor imaging of high-grade gliomas and metastatic brain tumors.

Authors:  Stanley Lu; Daniel Ahn; Glyn Johnson; Soonmee Cha
Journal:  AJNR Am J Neuroradiol       Date:  2003-05       Impact factor: 3.825

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  19 in total

1.  Geodesic shape regression in the framework of currents.

Authors:  James Fishbaugh; Marcel Prastawa; Guido Gerig; Stanley Durrleman
Journal:  Inf Process Med Imaging       Date:  2013

2.  Comparison of acute and chronic traumatic brain injury using semi-automatic multimodal segmentation of MR volumes.

Authors:  Andrei Irimia; Micah C Chambers; Jeffry R Alger; Maria Filippou; Marcel W Prastawa; Bo Wang; David A Hovda; Guido Gerig; Arthur W Toga; Ron Kikinis; Paul M Vespa; John D Van Horn
Journal:  J Neurotrauma       Date:  2011-09-21       Impact factor: 5.269

3.  Modeling 4D Pathological Changes by Leveraging Normative Models.

Authors:  Bo Wang; Marcel Prastawa; Andrei Irimia; Avishek Saha; Wei Liu; S Y Matthew Goh; Paul M Vespa; John D Van Horn; Guido Gerig
Journal:  Comput Vis Image Underst       Date:  2016-10       Impact factor: 3.876

4.  Automatic brain segmentation using fractional signal modeling of a multiple flip angle, spoiled gradient-recalled echo acquisition.

Authors:  André Ahlgren; Ronnie Wirestam; Freddy Ståhlberg; Linda Knutsson
Journal:  MAGMA       Date:  2014-03-18       Impact factor: 2.310

5.  Modeling 4D Changes in Pathological Anatomy using Domain Adaptation: Analysis of TBI Imaging using a Tumor Database.

Authors:  Bo Wang; Marcel Prastawa; Avishek Saha; Suyash P Awate; Andrei Irimia; Micah C Chambers; Paul M Vespa; John D Van Horn; Valerio Pascucci; Guido Gerig
Journal:  Multimodal Brain Image Anal (2013)       Date:  2013

6.  Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology.

Authors:  Andreas Mang; Spyridon Bakas; Shashank Subramanian; Christos Davatzikos; George Biros
Journal:  Annu Rev Biomed Eng       Date:  2020-06-04       Impact factor: 9.590

7.  Coupling brain-tumor biophysical models and diffeomorphic image registration.

Authors:  Klaudius Scheufele; Andreas Mang; Amir Gholami; Christos Davatzikos; George Biros; Miriam Mehl
Journal:  Comput Methods Appl Mech Eng       Date:  2019-01-07       Impact factor: 6.756

8.  A generative approach for image-based modeling of tumor growth.

Authors:  Bjoern H Menze; Koen Van Leemput; Antti Honkela; Ender Konukoglu; Marc-André Weber; Nicholas Ayache; Polina Golland
Journal:  Inf Process Med Imaging       Date:  2011

9.  Statistical approach for brain cancer classification using a region growing threshold.

Authors:  Bassam Al-Naami; Adnan Bashir; Hani Amasha; Jamal Al-Nabulsi; Abdul-Majeed Almalty
Journal:  J Med Syst       Date:  2009-10-16       Impact factor: 4.460

10.  Low-Rank Atlas Image Analyses in the Presence of Pathologies.

Authors:  Xiaoxiao Liu; Marc Niethammer; Roland Kwitt; Nikhil Singh; Matt McCormick; Stephen Aylward
Journal:  IEEE Trans Med Imaging       Date:  2015-06-22       Impact factor: 10.048

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