Elucidation of Differential Nano-Textural Attributes for Normal Oral Mucosa and Pre-Cancer
| Autor: | Jyotirmoy Chatterjee, Ranjan Rashmi Paul, Debjani Chakraborty, Anji Anura, Debaleena Nawn, Saunak Chatterjee, Mousumi Pal, Swarnendu Bag |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Normal oral mucosa
Local binary patterns Matrix (biology) Microscopy Atomic Force Sensitivity and Specificity 03 medical and health sciences 0302 clinical medicine Image Processing Computer-Assisted medicine Humans Computational analysis Oral mucosa Instrumentation 030304 developmental biology Microscopy 0303 health sciences Chemistry Atomic force microscopy Mouth Mucosa Sem analysis Cancer medicine.disease medicine.anatomical_structure 030220 oncology & carcinogenesis Microscopy Electron Scanning Precancerous Conditions Biomedical engineering |
| Zdroj: | Microscopy and Microanalysis. 25:1224-1233 |
| ISSN: | 1435-8115 1431-9276 |
| Popis: | Computational analysis on altered micro-nano-textural attributes of the oral mucosa may provide precise diagnostic information about oral potentially malignant disorders (OPMDs) instead of an existing handful of qualitative reports. This study evaluated micro-nano-textural features of oral epithelium from scanning electron microscopic (SEM) images and the sub-epithelial connective tissue from light microscopic (LM) and atomic force microscopic (AFM) images for normal and OPMD (namely oral sub-mucous fibrosis, i.e., OSF). Objective textural descriptors, namely discrete wavelet transform, gray-level co-occurrence matrix (GLCM), and local binary pattern (LBP), were extracted and fed to standard classifiers. Best classification accuracy of 87.28 and 93.21%; sensitivity of 93 and 96%; specificity of 80 and 91% were achieved, respectively, for SEM and AFM. In the study groups, SEM analysis showed a significant (p < 0.01) variation for all the considered textural descriptors, while for AFM, a remarkable alteration (p < 0.01) was only found in GLCM and LBP. Interestingly, sub-epithelial collagen nanoscale and microscale textural information from AFM and LM images, respectively, were complementary, namely microlevel contrast was more in normal (0.251) than OSF (0.193), while nanolevel contrast was more in OSF (0.283) than normal (0.204). This work, thus, illustrated differential micro-nano-textural attributes for oral epithelium and sub-epithelium to distinguish OPMD precisely and may be contributory in early cancer diagnostics. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|