Drug investigation tool: Identifying the effect of drug on cell image by using improved correlation
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Iqbal, Muhammad Shahid | - |
dc.contributor.author | Ahmad, Iftikhar | - |
dc.contributor.author | Asif, Muhammad | - |
dc.contributor.author | Kim, Sun-Hee | - |
dc.contributor.author | Mehmood, Raja Majid | - |
dc.date.accessioned | 2021-08-30T03:30:56Z | - |
dc.date.available | 2021-08-30T03:30:56Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2021-02 | - |
dc.identifier.issn | 0038-0644 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/49684 | - |
dc.description.abstract | In the treatment of human cancer, the existing drug response identification and assessment methods have some issues, such as high cost, slow processing, and low accuracy. Responsive methods that easily and indirectly assess patient tissue response to drugs or small molecules offer promising options for improving drug safety, and they are able to identify the right treatment for specific patients. Digital image correlation is a good technique that detects a part of the image between two images. In this article, a new method of correlation called significant improvement of correlation (SIC) was proposed. Data were taken from the confocal microscopy of two-photon excited fluorescence (TPEF) probe images taken every 5 min for short-term monitoring (STM) and long-term monitoring (LTM; 12, 24, and 48 hours). Cells were cultured, and a new compound TPEF was tested and injected the drug. The effect of drug on the TPEF compound was assessed through correlation. Experimental and simulation results showed that the proposed SIC was better than the conventional correlation method. Results also revealed that the first three images had 0.8% correlation in STM and LTM Image15 and Image10 had 0.49% correlation. The other images demonstrated minimum correlation. Thus, the effect of the newly made drug on the cell and image had a minimum correlation. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | WILEY | - |
dc.subject | ATOMIC-FORCE MICROSCOPY | - |
dc.subject | FIELD-MEASUREMENTS | - |
dc.subject | DEFORMATION | - |
dc.subject | CLASSIFICATION | - |
dc.subject | RECOGNITION | - |
dc.subject | DOXORUBICIN | - |
dc.subject | SPECKLE | - |
dc.title | Drug investigation tool: Identifying the effect of drug on cell image by using improved correlation | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Sun-Hee | - |
dc.identifier.doi | 10.1002/spe.2903 | - |
dc.identifier.scopusid | 2-s2.0-85092208642 | - |
dc.identifier.wosid | 000577470000001 | - |
dc.identifier.bibliographicCitation | SOFTWARE-PRACTICE & EXPERIENCE, v.51, no.2, pp.260 - 270 | - |
dc.relation.isPartOf | SOFTWARE-PRACTICE & EXPERIENCE | - |
dc.citation.title | SOFTWARE-PRACTICE & EXPERIENCE | - |
dc.citation.volume | 51 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 260 | - |
dc.citation.endPage | 270 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Software Engineering | - |
dc.subject.keywordPlus | ATOMIC-FORCE MICROSCOPY | - |
dc.subject.keywordPlus | FIELD-MEASUREMENTS | - |
dc.subject.keywordPlus | DEFORMATION | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
dc.subject.keywordPlus | RECOGNITION | - |
dc.subject.keywordPlus | DOXORUBICIN | - |
dc.subject.keywordPlus | SPECKLE | - |
dc.subject.keywordAuthor | drug investigation tool | - |
dc.subject.keywordAuthor | image correlation | - |
dc.subject.keywordAuthor | long-term monitoring | - |
dc.subject.keywordAuthor | short-term monitoring | - |
dc.subject.keywordAuthor | significant improvement of correlation | - |
dc.subject.keywordAuthor | two-photon excited florescence | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.