Comparison of Supervised and Unsupervised Deep Learning Methods for Medical Image Synthesis between Computed Tomography and Magnetic Resonance Images.

BioMed Research International
Yafen LiYaoqin Xie

Abstract

Cross-modality medical image synthesis between magnetic resonance (MR) images and computed tomography (CT) images has attracted increasing attention in many medical imaging area. Many deep learning methods have been used to generate pseudo-MR/CT images from counterpart modality images. In this study, we used U-Net and Cycle-Consistent Adversarial Networks (CycleGAN), which were typical networks of supervised and unsupervised deep learning methods, respectively, to transform MR/CT images to their counterpart modality. Experimental results show that synthetic images predicted by the proposed U-Net method got lower mean absolute error (MAE), higher structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR) in both directions of CT/MR synthesis, especially in synthetic CT image generation. Though synthetic images by the U-Net method has less contrast information than those by the CycleGAN method, the pixel value profile tendency of the synthetic images by the U-Net method is closer to the ground truth images. This work demonstrated that supervised deep learning method outperforms unsupervised deep learning method in accuracy for medical tasks of MR/CT synthesis.

References

Sep 21, 2004·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Zhou WangEero P Simoncelli
Nov 20, 2009·IEEE Transactions on Medical Imaging·Stefan KleinJosien P W Pluim
Jun 17, 2014·Seminars in Radiation Oncology·Piet DirixVincent Vandecaveye
Jul 24, 2014·IEEE Transactions on Medical Imaging·Ninon BurgosSebastien Ourselin
Oct 29, 2015·Physics in Medicine and Biology·Maria A Schmidt, Geoffrey S Payne
May 28, 2016·Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine·Yao WuWufan Chen
Sep 20, 2017·Radiology·Fang LiuAlan B McMillan
Oct 6, 2017·IEEE Transactions on Medical Imaging·Pedro CostaAurelio Campilho
Jan 1, 2016·Deep Learning and Data Labeling for Medical Applications : First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings·Dong NieDinggang Shen
May 24, 2018·Physics in Medicine and Biology·Kuang GongQuanzheng Li
Aug 16, 2018·International Journal of Radiation Oncology, Biology, Physics·Anna M DinklaCornelis A T van den Berg
Aug 16, 2018·Physics in Medicine and Biology·Matteo MasperoCornelis A T van den Berg
Mar 13, 2019·Journal of Applied Clinical Medical Physics·Fang LiuAlan B McMillan

❮ Previous
Next ❯

Citations


❮ Previous
Next ❯

Software Mentioned

Elastix
Net
CycleGAN

Related Concepts

Trending Feeds

COVID-19

Coronaviruses encompass a large family of viruses that cause the common cold as well as more serious diseases, such as the ongoing outbreak of coronavirus disease 2019 (COVID-19; formally known as 2019-nCoV). Coronaviruses can spread from animals to humans; symptoms include fever, cough, shortness of breath, and breathing difficulties; in more severe cases, infection can lead to death. This feed covers recent research on COVID-19.

Blastomycosis

Blastomycosis fungal infections spread through inhaling Blastomyces dermatitidis spores. Discover the latest research on blastomycosis fungal infections here.

Nuclear Pore Complex in ALS/FTD

Alterations in nucleocytoplasmic transport, controlled by the nuclear pore complex, may be involved in the pathomechanism underlying multiple neurodegenerative diseases including Amyotrophic Lateral Sclerosis and Frontotemporal Dementia. Here is the latest research on the nuclear pore complex in ALS and FTD.

Applications of Molecular Barcoding

The concept of molecular barcoding is that each original DNA or RNA molecule is attached to a unique sequence barcode. Sequence reads having different barcodes represent different original molecules, while sequence reads having the same barcode are results of PCR duplication from one original molecule. Discover the latest research on molecular barcoding here.

Chronic Fatigue Syndrome

Chronic fatigue syndrome is a disease characterized by unexplained disabling fatigue; the pathology of which is incompletely understood. Discover the latest research on chronic fatigue syndrome here.

Evolution of Pluripotency

Pluripotency refers to the ability of a cell to develop into three primary germ cell layers of the embryo. This feed focuses on the mechanisms that underlie the evolution of pluripotency. Here is the latest research.

Position Effect Variegation

Position Effect Variagation occurs when a gene is inactivated due to its positioning near heterochromatic regions within a chromosome. Discover the latest research on Position Effect Variagation here.

STING Receptor Agonists

Stimulator of IFN genes (STING) are a group of transmembrane proteins that are involved in the induction of type I interferon that is important in the innate immune response. The stimulation of STING has been an active area of research in the treatment of cancer and infectious diseases. Here is the latest research on STING receptor agonists.

Microbicide

Microbicides are products that can be applied to vaginal or rectal mucosal surfaces with the goal of preventing, or at least significantly reducing, the transmission of sexually transmitted infections. Here is the latest research on microbicides.

Related Papers

Current Medical Imaging
Khalid Raza, Nripendra Kumar Singh
IEEE Transactions on Neural Networks and Learning Systems
Maoguo GongLicheng Jiao
Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society
Satoru MizusawaAkihiko Ohsuga
© 2021 Meta ULC. All rights reserved