Healthcare Professional in the Loop (HPIL): Classification of Standard and Oral Cancer-Causing Anomalous Regions of Oral Cavity Using Textural Analysis Technique in Autofluorescence Imaging.

Muhammad Awais,Anitha Krishnan Pandarathodiyil,Ibrahima Faye,Mohamad Naufal Saad,Sharnil Pandya,Anand Ramanathan,Rosnah Binti Zain,Hemant Ghayvat,Nicolas Walter,Wan Maria Nabillah Ghani

doi:10.3390/s20205780

Abstract

Oral mucosal lesions (OML) and oral potentially malignant disorders (OPMDs) have been identified as having the potential to transform into oral squamous cell carcinoma (OSCC). This research focuses on the human-in-the-loop-system named Healthcare Professionals in the Loop (HPIL) to support diagnosis through an advanced machine learning procedure. HPIL is a novel system approach based on the textural pattern of OML and OPMDs (anomalous regions) to differentiate them from standard regions of the oral cavity by using autofluorescence imaging. An innovative method based on pre-processing, e.g., the Deriche–Canny edge detector and circular Hough transform (CHT); a post-processing textural analysis approach using the gray-level co-occurrence matrix (GLCM); and a feature selection algorithm (linear discriminant analysis (LDA)), followed by k-nearest neighbor (KNN) to classify OPMDs and the standard region, is proposed in this paper. The accuracy, sensitivity, and specificity in differentiating between standard and anomalous regions of the oral cavity are 83%, 85%, and 84%, respectively. The performance evaluation was plotted through the receiver operating characteristics of periodontist diagnosis with the HPIL system and without the system. This method of classifying OML and OPMD areas may help the dental specialist to identify anomalous regions for performing their biopsies more efficiently to predict the histological diagnosis of epithelial dysplasia.

Highlights

The proposed Healthcare Professional in the loop (HPIL) model acts as an aided tool for periodontists by automatically analyzing the VELscope® image of an oral cavity to find the region of interest (ROI)
VELscope® device device circular region appeared in in aa number number of of images; images; this this noisy noisy region region observed device circular circular region region appeared observed that the VELscope
The classification of anomalous (OML and oral potentially malignant disorders (OPMDs)) and specific regions using autofluorescence images with the help of textual analysis and feature selection represents a novel way of identifying the ROI for biopsy

Summary

Introduction

Oral potentially malignant (OPMDs) are onedisorders of the severe health issues across the ®lesions; autofluorescence imaging; texture analysis; VELscope globe [1]. Oral potentially malignant (OPMDs) are onedisorders of the severe health issues across the ®. The detection and diagnosis of these OPMDs as early as possible are. Screening for oral cavities implies searching for OPMDs and OML, typically before symptoms occur. The following steps have been followed by clinicians for screening and diagnosis inside the oral cavity. 1. Determining the background history of existing disease (if any): (a) the beginning, place, strength, occurrence, and period; (b) any irritation or discharges; (c) whether the disease has improved, remained constant, or worsened over the period. 2. Medical and drugs history (if any):. (a) medical circumstances; (b) medications and antipathies; (c) tobacco and alcohol history (nature and time). 3. Medical examination: (a) extra mouth-cavity screening; (b) an intraoral check-up;

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