Total Variation Algorithms for PAT Image Reconstruction

Mary Josy John, Imad Barhumi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Medical imaging is an essential part of disease diagnosis, which makes use of technologies such as X-ray, Magnetic Resonance Imaging (MRI), Ultrasound scan, and many more. X-rays are ionizing radiation and cannot be used for frequent examinations, whereas MRI is non-ionizing, but it is costly and time-consuming. Ultrasound scan is frequently used in scanning and is noninvasive but suffers from the problem of low image quality, which can lead to incorrect diagnoses. The efficiency of these methods depends on how invasive, fast, and accurate the imaging method is. Recently, a new method called Photoacoustic Tomography (PAT) is gaining attention due to its ability to produce images with high resolution and high contrast in long penetration depths. A system matrix could be developed from the pseudospectral matrix by evaluating it on different time samples for different sensor locations. Compressive Sensing (CS) algorithms can thus be developed using the system matrix obtained, and their performance could be evaluated. CS is based on how sparse the reconstruction could be. This is mainly based on the regularizer used along with the prior information. In this paper, we propose split Bregman formulation of isotropic and anisotropic total variation with l1 and l2 regularization for efficient PAT image reconstruction. The proposed methods have better reconstruction efficiency in terms of computation time and image quality while maintaining the sparsity. When evaluating the various TV formulations for PAT image reconstruction, it is observed that anisotropic TV-l2 is the most efficient one, generating superior image quality and accomplishing the reconstruction in less than 1 second, enabling quick medical imaging and early diagnosis.

Original languageEnglish
Title of host publicationProceedings of 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1164-1168
Number of pages5
ISBN (Electronic)9786165904773
DOIs
Publication statusPublished - 2022
Event2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022 - Chiang Mai, Thailand
Duration: Nov 7 2022Nov 10 2022

Publication series

NameProceedings of 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022

Conference

Conference2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022
Country/TerritoryThailand
CityChiang Mai
Period11/7/2211/10/22

Keywords

  • Cancer Detection
  • Compressive Sensing
  • Photoacoustic Tomography
  • Split Bregman
  • Total variation

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

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