Perovskite materials in X-ray detection and imaging: recent progress, challenges, and future prospects-Reference-Cited by-同舟云学术

Perovskite materials in X-ray detection and imaging: recent progress, challenges, and future prospects

Published:2024 Issue:10 Volume:14 Page:6656-6698
ISSN:2046-2069
Container-title:RSC Advances
language:en
Short-container-title:RSC Adv.

Author:

Miah Md. Helal¹²^ORCID,Khandaker Mayeen Uddin¹³^ORCID,Aminul Islam Mohammad⁴,Nur-E-Alam Mohammad⁵⁶,Osman Hamid⁷^ORCID,Ullah Md. Habib⁸^ORCID

Affiliation:

1. Applied Physics and Radiation Technologies Group, CCDCU, School of Engineering and Technology, Sunway University, Bandar Sunway 47500, Selangor, Malaysia

2. Department of Physics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj 8100, Bangladesh

3. Faculty of Graduate Studies, Daffodil International University, Daffodil Smart City, Birulia, Savar, Dhaka, 1216, Bangladesh

4. Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur 50603, Selangor, Malaysia

5. Institute of Sustainable Energy, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, Kajang 43000, Selangor, Malaysia

6. School of Science, Edith Cowan University, 270 Joondalup Drive, Joondalup-6027, WA, Australia

7. Department of Radiological Sciences, College of Applied Medical Sciences, Taif University, 21944 Taif, Saudi Arabia

8. Department of Physics, Faculty of Science and Technology, American International University-Bangladesh, 408/1, Kuratoli, Khilkhet, Dhaka 1229, Bangladesh

Abstract

Perovskite-based X-ray detection and imaging have reached new milestones due to rapid advancements in evolution of materials, cost-effective fabrication techniques, and architectural modifications in device design.

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/RA/D4RA00433G

Reference209 articles.

1. Recent advances in X-ray photoconductors for direct conversion X-ray image detectors

2. Perovskite semiconductors for direct X-ray detection and imaging

3. Deep co-supervision and attention fusion strategy for automatic COVID-19 lung infection segmentation on CT images

4. CT imaging of the COVID-19

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