• Login
    View Item 
    •   etd@IISc
    • Division of Interdisciplinary Research
    • Supercomputer Education and Research Centre (SERC)
    • View Item
    •   etd@IISc
    • Division of Interdisciplinary Research
    • Supercomputer Education and Research Centre (SERC)
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Development of Next Generation Image Reconstruction Algorithms for Diffuse Optical and Photoacoustic Tomography

    View/Open
    G26344.pdf (12.22Mb)
    Date
    2018-02-15
    Author
    Jaya Prakash, *
    Metadata
    Show full item record
    Abstract
    Biomedical optical imaging is capable of providing functional information of the soft bi-ological tissues, whose applications include imaging large tissues, such breastand brain in-vivo. Biomedical optical imaging uses near infrared light (600nm-900nm) as the probing media, givin ganaddedadvantageofbeingnon-ionizingimagingmodality. The tomographic technologies for imaging large tissues encompasses diffuse optical tomogra-phyandphotoacoustictomography. Traditional image reconstruction methods indiffuse optical tomographyemploysa �2-norm based regularization, which is known to remove high frequency no is either econstructed images and make the mappearsmooth. Hence as parsity based image reconstruction has been deployed for diffuse optical tomography, these sparserecov-ery methods utilize the �p-norm based regularization in the estimation problem with 0≤ p<1. These sparse recovery methods, along with an approximation to utilizethe �0-norm, have been used forther econstruction of diffus eopticaltomographic images.The comparison of these methods was performed by increasing the sparsityinthesolu-tion. Further a model resolution matrix based framework was proposed and shown to in-duceblurinthe�2-norm based regularization framework for diffuse optical tomography. This model-resolution matrix framework was utilized in the optical imaged econvolution framework. A basis pursuitdeconvolution based on Split AugmentedLagrangianShrink-ageAlgorithm(SALSA)algorithm was used along with the Tikhonovregularization step making the image reconstruction into a two-step procedure. This new two-step approach was found to be robust with no iseandwasabletobetterdelineatethestructureswhichwasevaluatedusingnumericalandgelatinphantom experiments. Modern diffuse optical imaging systems are multi-modalin nature, where diffuse optical imaging is combined with traditional imaging modalitiessuc has Magnetic Res-onanceImaging(MRI),or Computed Tomography(CT). Image-guided diffuse optical tomography has the advantage of reducingthetota lnumber of optical parameters beingreconstructedtothenumber of distinct tissue types identified by the traditional imaging modality, converting the optical image-reconstruction problem fromunder-determined innaturetoover-determined. In such cases, the minimum required measurements might be farless compared to those of the traditional diffuse optical imaging. An approach to choose these measurements optimally based on a data-resolution matrix is proposed, and it is shown that it drastically reduces the minimum required measurements (typicalcaseof240to6) without compromising the image reconstruction performance. In the last part of the work , a model-based image reconstruction approaches in pho-toacoustic tomography (which combines light and ultra sound) arestudied as it is know that these methods have a distinct advantage compared to traditionalanalytical methods in limited datacase. These model-based methods deployTikhonovbasedregularizationschemetoreconstruct the initial pressure from the boundary acoustic data. Again a model-resolution for these cases tend to represent the blurinduced by the regularization scheme. A method that utilizes this blurringmodelandper forms the basis pursuit econ-volution to improve the quantitative accuracy of the reconstructed photoacoustic image is proposed and shown to be superior compared to other traditional methods. Moreover, this deconvolution including the building of model-resolution matrixis achievedvia the Lanczosbidiagonalization (least-squares QR) making this approach computationally ef-ficient and deployable inreal-time. Keywords Medical imaging, biomedical optical imaging, diffuse optical tomography, photoacous-tictomography, multi-modalimaging, inverse problems,sparse recovery,computational methods inbiomedical optical imaging.
    URI
    https://etd.iisc.ac.in/handle/2005/3112
    Collections
    • Supercomputer Education and Research Centre (SERC) [98]

    Related items

    Showing items related by title, author, creator and subject.

    • Design and Analysis of Integrated Optic Waveguide Delay Line Phase Shifters for Microwave Photonic Application 

      Honnungar, Rajini V (2018-04-23)
      Microwave Photonics(MWP) has been defined as the study of photonic devices which operate at microwave frequencies and also their applications to microwave and optical systems. One or more electrical signals at microwave ...
    • Experimental And Theoretical Studies Towards The Development Of A Direct 3-D Diffuse Optical Tomographic Imaging System 

      Biswas, Samir Kumar (2014-06-02)
      Diffuse Optical Tomography is a diagnostic imaging modality where optical parameters such as absorption coefficient, scattering coefficient and refractive index distributions are recovered to form the internal tissue ...
    • Development of Novel Reconstruction Methods Based on l1--Minimization for Near Infrared Diffuse Optical Tomography 

      Shaw, Calbvin B (2018-03-03)
      Diffuse optical tomography uses near infrared (NIR) light as the probing media to recover the distributions of tissue optical properties. It has a potential to become an adjunct imaging modality for breast and brain imaging, ...

    etd@IISc is a joint service of SERC & J R D Tata Memorial (JRDTML) Library || Powered by DSpace software || DuraSpace
    Contact Us | Send Feedback | Thesis Templates
    Theme by 
    Atmire NV
     

     

    Browse

    All of etd@IIScCommunities & CollectionsTitlesAuthorsAdvisorsSubjectsBy Thesis Submission DateThis CollectionTitlesAuthorsAdvisorsSubjectsBy Thesis Submission Date

    My Account

    LoginRegister

    etd@IISc is a joint service of SERC & J R D Tata Memorial (JRDTML) Library || Powered by DSpace software || DuraSpace
    Contact Us | Send Feedback | Thesis Templates
    Theme by 
    Atmire NV