عنوان انگلیسی مقاله:
Computer vision techniques for Upper Aero-Digestive Tract tumor grading classification - Addressing pathological challenges
ترجمه فارسی عنوان مقاله:
تکنیک های بینایی ماشین برای طبقه بندی تومورهای دستگاه هضم دستگاه گوارش فوقانی - پرداختن به چالش های آسیب شناختی
Sciencedirect - Elsevier - Pattern Recognition Letters, 144 (2021) 42-53: doi:10:1016/j:patrec:2021:01:002
Oral cancer is one of the common cancer types which scales higher in death rate every year. The con- nectivity of two different cavities like oral cavity and nasal cavity is known as Upper Aero-Digestive Tract (UADT). Both oral and nasal cavities consist of thirteen connecting sites from mouth to upper stomach. The traditional pathological analysis like manual microscopic review brings out major intra and inter- observer variability problem. A new automated system is proposed using computer vision techniques to focus and analyse major pathological problems like intra and interobserver variability problem and mis- classiﬁcation of dysplasia type of tumours. The morphological behaviour of biopsy tissue samples are analysed digitally with different sites of UADT and different cancerous and non-cancerous stages. The proposed technique will play a major role in assisting the manual pathology procedure for analysing the morphology of dysplasia type of tumours and classiﬁcation of tumour gradings. A method is proposed which integrates an alternate process to ﬁnd the morphology of dysplasia type tumours using different image processing techniques. A state-of-the-art Force Reconstructed Particle Swarm Optimization Based SVM is proposed for UADT oral cancer classiﬁcation for ten different oral cavity sites. The proposed clas- siﬁcation technique achieved 94 % accuracy.© 2021 Elsevier B.V. All rights reserved.
Keywords: FR-PSO | SVM | Classification | Cancer | UADT | Machine Learning