Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/142301
DC Field | Value | |
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dc.title | ACCOUNTING FOR NON-IDENTICAL DATA IN BIOIMAGE INFORMATICS | |
dc.contributor.author | SWAMINATHAN MUTHUKARUPPAN | |
dc.date.accessioned | 2018-05-23T18:00:20Z | |
dc.date.available | 2018-05-23T18:00:20Z | |
dc.date.issued | 2018-01-22 | |
dc.identifier.citation | SWAMINATHAN MUTHUKARUPPAN (2018-01-22). ACCOUNTING FOR NON-IDENTICAL DATA IN BIOIMAGE INFORMATICS. ScholarBank@NUS Repository. | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/142301 | |
dc.description.abstract | Bio-image informatics involves developing computational methods to analyze microscopic images in biological studies. The underlying assumption in these methods is that data are independent and identically distributed. However, in real-world settings, data generally originate from heterogeneous sources even if they do possess a common data-generating mechanism. Since these sources are not identically distributed by necessity, the assumption of identical distribution is inappropriate. Here, we have proposed a distance measure called Poisson-Binomial Radius (PBR) to account for non-identical data. Results from image classification and recognition experiments demonstrate that PBR outperforms state-of-the-art distance measures. Furthermore, we have used the PBR principle to design an automated pattern recognition system for detecting nasopharyngeal carcinoma using indirect immunofluorescence images. This new framework allows clear-cut cases (which are in the majority) to be machine-evaluated, hence freeing pathology staff to concentrate solely on the difficult cases. | |
dc.language.iso | en | |
dc.subject | Bioimage informatics, machine learning, non-identical data, image classification, distance measures | |
dc.type | Thesis | |
dc.contributor.department | BIOLOGICAL SCIENCES | |
dc.contributor.supervisor | Cheong Shen-Yi, Ian | |
dc.description.degree | Ph.D | |
dc.description.degreeconferred | DOCTOR OF PHILOSOPHY (FOS) | |
Appears in Collections: | Ph.D Theses (Open) |
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SwaminathanM.pdf | 9.86 MB | Adobe PDF | OPEN | None | View/Download |
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