Automated analysis and investigation of digital microscopic images of urine sediments for detection and classification of urinary particles
| dc.contributor.guide | Brindha D | |
| dc.coverage.spatial | Automated analysis and investigation of digital microscopic images of urine sediments for detection and classification of urinary particles | |
| dc.creator.researcher | Suhail K | |
| dc.date.accessioned | 2025-11-17T04:22:17Z | |
| dc.date.available | 2025-11-17T04:22:17Z | |
| dc.date.awarded | 2025 | |
| dc.date.completed | 2025 | |
| dc.date.registered | ||
| dc.description.abstract | The kidney and urinary tract related problems are the most commonly diagnosed diseases globally in an annum. There is a large surge is identified in the spreading of various kidney and urinary tract abnormalities such as UTIs, kidney stones, bladder inflammations, glomerulonephritis, etc. The timely detection and treatment of such abnormalities are very important for the patients who is suffering such diseases. The microscopic analysis of urine sediments is the widely used technique for the early identification of kidney or urinary tract abnormalities. The existence of various microscopic particles such as erythrocytes, leukocytes, crystals, casts, bacteria, yeast, epithelial cells, etc in the urine sediment are the indication for various diseases related to kidney and ariary tract. newlineThe traditional method used for the analysis of urine sediment examination was centrifugation, in which the urine sediments are collected in a centrifuge to find the particles manually by a clinical expert. This approach is time and effort intensive and it requires high volume laboratories to perform the task. The automated microscopic examination is performed to address the cons associated with the manual examination by utilizing digital microscopic urine sediment images. newline | |
| dc.description.note | ||
| dc.format.accompanyingmaterial | None | |
| dc.format.dimensions | 21cm | |
| dc.format.extent | xviii,164p. | |
| dc.identifier.researcherid | ||
| dc.identifier.uri | http://hdl.handle.net/10603/673794 | |
| dc.language | English | |
| dc.publisher.institution | Faculty of Information and Communication Engineering | |
| dc.publisher.place | Chennai | |
| dc.publisher.university | Anna University | |
| dc.relation | p.147-163 | |
| dc.rights | university | |
| dc.source.university | University | |
| dc.subject.keyword | Digital Microscopic Images | |
| dc.subject.keyword | Urine Sediments | |
| dc.subject.keyword | YOLO algorithms | |
| dc.title | Automated analysis and investigation of digital microscopic images of urine sediments for detection and classification of urinary particles | |
| dc.title.alternative | ||
| dc.type.degree | Ph.D. |
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