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Pan CT, Chang WH, Kumar A, Singh SP, Kaushik AC, Sharma J, Long ZJ, Wen ZH, Mishra SK, Yen CK, Chaudhary RK, Shiue YL. Nanoparticles-mediated Brain Imaging and Disease Prognosis by Conventional as well as Modern Modal Imaging Techniques: a Comparison. Curr Pharm Des 2020; 25:2637-2649. [PMID: 31603057 DOI: 10.2174/1381612825666190709220139] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2019] [Accepted: 07/02/2019] [Indexed: 12/27/2022]
Abstract
BACKGROUND Multimodal imaging plays an important role in the diagnosis of brain disorders. Neurological disorders need to be diagnosed at an early stage for their effective treatment as later, it is very difficult to treat them. If possible, diagnosing at an early stage can be much helpful in curing the disease with less harm to the body. There is a need for advanced and multimodal imaging techniques for the same. This paper provides an overview of conventional as well as modern imaging techniques for brain diseases, specifically for tumor imaging. In this paper, different imaging modalities are discussed for tumor detection in the brain along with their advantages and disadvantages. Conjugation of two and more than two modalities provides more accurate information rather than a single modality. They can monitor and differentiate the cellular processes of normal and diseased condition with more clarity. The advent of molecular imaging, including reporter gene imaging, has opened the door of more advanced noninvasive detection of brain tumors. Due to specific optical properties, semiconducting polymer-based nanoparticles also play a pivotal role in imaging tumors. OBJECTIVE The objective of this paper is to review nanoparticles-mediated brain imaging and disease prognosis by conventional as well as modern modal imaging techniques. CONCLUSION We reviewed in detail various medical imaging techniques. This paper covers recent developments in detail and elaborates a possible research aspect for the readers in the field.
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Affiliation(s)
- Cheng-Tang Pan
- Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-Sen University, Kaohsiung City 804, Taiwan.,Institute of Medical Science and Technology, National Sun Yat-Sen University, Kaohsiung City 804, Taiwan
| | - Wei-Hsi Chang
- Department of Emergency Medicine, Kaohsiung Armed Forces General Hospital, Kaohsiung, Taiwan
| | - Ajay Kumar
- Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-Sen University, Kaohsiung City 804, Taiwan.,Institute of Biomedical Sciences, National Sun Yat-Sen University, Kaohsiung City 804, Taiwan
| | - Satya P Singh
- School of EEE, Nanyang Technological University, Nanyang Ave, Singapore
| | - Aman Chandra Kaushik
- State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, ShanghaiJia Tong University, Shanghai 200240, China
| | - Jyotsna Sharma
- Amity School of Applied Sciences, Amity University Haryana, Gurugram-122413, Manesai, Panchgaon, Haryana, India
| | - Zheng-Jing Long
- Department of Emergency Medicine, Kaohsiung Armed Forces General Hospital, Kaohsiung, Taiwan
| | - Zhi-Hong Wen
- Department of Marine Biotechnology and Resources, National Sun Yat-Sen University, Kaohsiung, Taiwan
| | - Sunil Kumar Mishra
- Patronage Institute of Management Studies, Greater Noida, Uttar Pradesh, India
| | - Chung-Kun Yen
- Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-Sen University, Kaohsiung City 804, Taiwan
| | - Ravi Kumar Chaudhary
- School of Biotechnology, Gautam Buddha University, Greater Noida, Uttar Pardesh, India, India
| | - Yow-Ling Shiue
- Institute of Biomedical Sciences, National Sun Yat-Sen University, Kaohsiung City 804, Taiwan
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Urooj S, Singh SP. Wavelet Transform-Based Soft Computational Techniques and Applications in Medical Imaging. Biometrics 2017. [DOI: 10.4018/978-1-5225-0983-7.ch038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The aim of this chapter is to highlight the biomedical applications of wavelet transform based soft computational techniques i.e. wavenet and corresponding research efforts in imaging techniques. A brief introduction of wavelet transform, its properties that are vital for biomedical applications touched by various researchers and basics of neural networks has been discussed. The concept of wavelon and wavenet is also discussed in detail. Recent survey of wavelet based neural networks in medical imaging is another facet of this script, which includes biomedical image denoising, image enhancement and functional neuro-imaging, including positron emission tomography and functional MRI.
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