Meibomian gland cyst detection and classification using hyperspectral imaging

Abstract

The primary role of the oily secretion (meibum) is to ensure tear film stability and retard evaporation. In addition to these is providing ocular surface lubrication, which is necessary for smooth eyelid movements. When a gland is blocked, it is described as a Meibomian gland cyst (MGC), which can be a meibomian cyst, usually referred to as chalazion (eye bump), or in the case of inflammation, it is considered to be a hordeolum (sty or stye). Topical ophthalmic ointments and eyelid heat massages can treat early diagnosed MGC; otherwise, surgical operation is required. The current techniques of diagnosing MGC are usually uncomfortable or invasive, such as examining the tarsal plate after everting the eyelid or by biopsy procedures. The purpose of this work is to propose a non-invasive MGC evaluation and classification technique using hyperspectral imaging and image processing. The proposed technique was carried out on a single patient (i.e., case study) for a period of 4 months to monitor the MGC evolution until postsurgery-recovery and was compared with a normal eyelid patient. The collected hypercube data were processed using Multivariate Curve Resolution (MCR) and image analysis to classify the MGC severity levels. The proposed work built the threshold of the complete system, where early diagnosis of an MGC is possible before it becomes visible to the eye, hence reducing the treatment duration and avoiding any further complications that require clinical lancing. Also, the system can be used as a postoperative check postsurgery to make sure the eyelid went back to normal.

Keywords

• chalazion
• hordeolum
• hyperspectral imaging
• image processing
• meibomian gland cyst
• meibomian cyst
• multivariate curve resolution
• sty