A new paradigm of oral cancer detection using digital infrared thermal imaging

Abstract

Histopathology is considered the gold standard for oral cancer detection. But a major fraction of patient population is incapable of accessing such healthcare facilities due to poverty. Moreover, such analysis may report false negatives when test tissue is not collected from exact cancerous location. The proposed work introduces a pioneering computer aided paradigm of fast, non-invasive and non-ionizing modality for oral cancer detection using Digital Infrared Thermal Imaging (DITI). Due to aberrant metabolic activities in carcinogenic facial regions, heat signatures of patients are different from that of normal subjects. The proposed work utilizes asymmetry of temperature distribution of facial regions as principle cue for cancer detection. Three views of a subject, viz. front, left and right are acquired using long infrared (7.5 − 13µm) camera for analysing distribution of temperature. We study asymmetry of facial temperature distribution between: a) left and right profile faces and b) left and right half of frontal face. Comparison of temperature distribution suggests that patients manifest greater asymmetry compared to normal subjects. For classification, we initially use k-means and fuzzy k-means for unsupervised clustering followed by cluster class prototype assignment based on majority voting. Average classification accuracy of 91.5% and 92.8% are achieved by k-mean and fuzzy k-mean framework for frontal face. The corresponding metrics for profile face are 93.4% and 95%. Combining features of frontal and profile faces, average accuracies are increased to 96.2% and 97.6% respectively for k-means and fuzzy k-means framework.

Sulforhodamine Nanothermometer for Multiparametric Fluorescence Lifetime Imaging Microscopy

“…Temperature ( T ) affects numerous physical, chemical, and biological processes in the cell, including production of energy, diffusion of biomolecules and drugs, viscosity, and enzymatic and acid–base reactions. − In higher multicellular organisms, tissue T is usually kept within narrow physiological limits via a number of pathways, including thermogenesis in skeletal muscle and brown adipose tissue. − The success of diagnostics and therapy of multitude of diseases, including cancer, is also highly dependent on careful control and imaging of temperature. , Therefore, tissue T is regarded as important marker for medical imaging and cancer biology.…”

Thermal imaging for cancer detection

“…Stefan-Boltzmann Law One of the fundamental equations in thermal imaging is the Stefan-Boltzmann law, which relates the total power radiated by an object to its temperature [12] . P = σεAT 4 (1…”

Study of morphological and textural features for classification of oral squamous cell carcinoma by traditional machine learning techniques

“…Studies of oral cancer on domains apart from microscopic images include endoscopic images of the esophagus where active contour‐based segmentation and fuzzy rule‐based classification were proposed 21 ; a quantitative histomorphometric classifier on oropharyngeal SCC 22 ; deep learning techniques on hyperspectral images 23,24 ; random forest and SVM on confocal laser endomicroscopy (CLE) images 25,26 ; combined machine learning (ML) techniques using asymmetry of a temperature distribution of facial regions as principle cue on digital infrared thermal imaging 27 . Hameed et al 28 proposed a novel cell nuclei feature extraction method for immunohistochemical scoring of oral cancer tissue images.…”