research-article

Structure-Enhanced Translation from PET to CT Modality with Paired GANs

Authors:

Md. Bakhtiar Hasan,

Md. Taslim Reza,

Md. Hasanul KabirAuthors Info & Claims

ICMVA '23: Proceedings of the 2023 6th International Conference on Machine Vision and Applications

Pages 142 - 146

https://doi.org/10.1145/3589572.3589593

Published: 09 June 2023 Publication History

Abstract

Computed Tomography (CT) images play a crucial role in medical diagnosis and treatment planning. However, acquiring CT images can be difficult in certain scenarios, such as patients inability to undergo radiation exposure or unavailability of CT scanner. An alternative solution can be generating CT images from other imaging modalities. In this work, we propose a medical image translation pipeline for generating high-quality CT images from Positron Emission Tomography (PET) images using a Pix2Pix Generative Adversarial Network (GAN), which are effective in image translation tasks. However, traditional GAN loss functions often fail to capture the structural similarity between generated and target image. To alleviate this issue, we introduce a Multi-Scale Structural Similarity Index Measure (MS-SSIM) loss in addition to the GAN loss to ensure that the generated images preserve the anatomical structures and patterns present in the real CT images. Experiments on the ‘QIN-Breast’ dataset demonstrate that our proposed architecture achieves a Peak Signal-to-Noise Ratio (PSNR) of 17.70 dB and a Structural Similarity Index Measure (SSIM) of 42.51% in the region of interest.

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Cited By

Tasmi SAhmed SSarker Raihan M(2023)Performance Analysis of Machine Learning Algorithms for Autism Spectrum Disorder Level Detection using Behavioural Symptoms2023 26th International Conference on Computer and Information Technology (ICCIT)10.1109/ICCIT60459.2023.10441249(1-6)Online publication date: 13-Dec-2023
https://doi.org/10.1109/ICCIT60459.2023.10441249

Index Terms

Structure-Enhanced Translation from PET to CT Modality with Paired GANs
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision

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Abstract
Medical image translation has the potential to reduce the imaging workload, by removing the need to capture some sequences, and to reduce the annotation burden for developing machine learning methods. GANs have been used successfully to translate ...

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cover image ACM Other conferences

ICMVA '23: Proceedings of the 2023 6th International Conference on Machine Vision and Applications

March 2023

193 pages

ISBN:9781450399531

DOI:10.1145/3589572

Copyright © 2023 ACM.

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Published: 09 June 2023

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ICMVA 2023

ICMVA 2023: 2023 The 6th International Conference on Machine Vision and Applications

March 10 - 12, 2023

Singapore, Singapore

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Cited By

Tasmi SAhmed SSarker Raihan M(2023)Performance Analysis of Machine Learning Algorithms for Autism Spectrum Disorder Level Detection using Behavioural Symptoms2023 26th International Conference on Computer and Information Technology (ICCIT)10.1109/ICCIT60459.2023.10441249(1-6)Online publication date: 13-Dec-2023
https://doi.org/10.1109/ICCIT60459.2023.10441249

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