editorial translational molecular imaging computing: advances … · 2019. 7. 30. · editorial...

EditorialTranslational Molecular Imaging Computing:Advances in Theories and Applications

Jinchao Feng,1 Wenxiang Cong,2 Kuangyu Shi,3 Shouping Zhu,4 and Jun Zhang5

1Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China2Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA3Department of Nuclear Medicine, Technical University of Munich, 81675 Munich, Germany4School of Life Science and Technology, Xidian University, Xi’an 710071, China5Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA

Correspondence should be addressed to Jinchao Feng; [email protected]

Received 27 November 2016; Accepted 27 November 2016

Copyright © 2016 Jinchao Feng et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Molecular imaging is capable of revealing cellular andmolec-ular features of organism and disease in vivo, meeting theincreasing demands in the noninvasive understanding of bio-logical processes. Computational technologies are essentialfor the development of cutting-edge molecular imaging. Inthe past, the advancement of molecular imaging computinghas been well recognized and continuously extends theapplication potential of molecular imaging.

The papers selected for this special issue represent recentprogress in molecular imaging computing, including appli-cations, high-performance computing technologies, methodand algorithm improvement, and review. All of these papersnot only provide novel ideas and state-of-the-art technologiesin the field but also facilitate future research for translationalmolecular imaging.

Computed tomography (CT) is one of the commonlyused imaging techniques. Now, the use of CT has increasedrapidly. However, it involves radiation doses during a CTexam, which are harmful to the patient. When the radiationdose decreases, the relative noise in CT images will increase,which deteriorate the image quality.Therefore, how to reduceCT scanning dose of patients while maintaining the sameimage quality is a challenging problem. L. Deng et al.improved a total variation minimization method to enhancethe image quality of CT by incorporating prior images. M. Liet al. presented an improved smoothed 𝑙

0-norm regulariza-

tion method to suppress artifacts and to obtain better edgepreservation in reconstructed images.

Optical tomography (OT) is one of the most sensitivemolecular imaging techniques and is especially suited forpreclinical studies. Systematic reviews of OT will improveresearchers’ understanding and skills in utilizing the tech-nique. B. Zhu and A. Godavarty reviewed technical aspectsof fluorescence-enhanced optical tomography (also calledfluorescence molecular tomography, FMT) including theprincipal, measurement approaches, forward model, andinverse problem.

B. Zhu and A. Godavarty mentioned that the inverseproblem of FMT is severally ill-posed and underdetermineddue to nonuniqueness and a limited number of measure-ments. To alleviate the ill-posedness of FMT, H. Yi et al.presented a feasible region extraction strategy based on adouble mesh. To increase computational efficiency, D. Chenet al. developed a sparsity-constrained preconditioned Kacz-marz reconstructionmethod. To improve the image quality ofFMT, H. Zhang et al. developed a reconstruction method byminimizing the difference between 𝐿

1and 𝐿

2norms (i.e.,

𝐿1-2-norm).Cherenkov luminescence imaging (CLI) is an emerging

imaging modality, which captures visible photons emitted byCherenkov radiation labeled with 𝛽-emitting radionuclidesusing widely available in vivo optical imaging systems. Inother words, CLI uses optical means to provide informationof medical radionuclides used in nuclear imaging basedon Cerenkov radiation. However, the exceptionally weakCerenkov luminescence from Cerenkov radiation is suscep-tible to lots of impulse noises. In the paper contributed

Hindawi Publishing CorporationBioMed Research InternationalVolume 2016, Article ID 1569605, 2 pageshttp://dx.doi.org/10.1155/2016/1569605

2 BioMed Research International

by X. Cao et al., a temporal median filter is proposed toremove this kind of impulse noises. Results of in vivo exper-iments demonstrated that the temporal median method caneffectively remove random pulse noises induced by gammaradiation and achieve a robust CLI image.

The image resolution of pure OT or CLT is relatively lowbecause of the high diffusion of photons in biological tissues.To improve image resolution, a new hybrid imagingmodality,X-ray luminescence computed tomography (XLCT), hasbeen developed. XLCT utilizes X-ray luminescent nanophos-phors (NPs) as imaging probes. NPs can be excited with apencil, fan, or cone beam of X-rays. Cone beam XLCT canrealize fast XLCTwith relatively low scanning time comparedwith pencil beamXLCT. However, the reconstruction of conebeam XLCT is also an ill-posed problem. To alleviate the ill-posedness of XLCT, D. Chen et al. developed a hybrid recon-struction algorithm with KA-FEM method. In vivo mouseexperiment was used to evaluate the feasibility of themethod.

Multimodality molecular imaging is now playing animportant role in preclinical and clinical research, which uti-lizes the strengths of different modalities and yields a hybridimaging platform with benefits superior to those of any ofits individual components, considered alone. In the papercontributed by Y. Liu et al., a dual-modality imaging sys-tem which combines multispectral photoacoustic computedtomography and ultrasound computed tomography wasdeveloped to reconstruct functional and structural informa-tion of human finger joint systems. Phantom and in vivoresults illustrated that the bones, the blood vessels, and thesubcutaneous tissues could be reconstructed using the dual-modality system.

Jinchao FengWenxiang Cong

Kuangyu ShiShouping Zhu

Jun Zhang

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editorial translational molecular imaging computing: advances … · 2019. 7. 30. · editorial...

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