## 1 Introduction  
Skin cancer is the most common group of cancers [1]. Its incidence, treatment costs, and associated health burden are steadily increasing [2, 3]. The most prevalent forms of skin cancer include basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and malignant melanoma (MM) [4]. Although MM accounts for approximately one in five skin cancers, it remains the most serious type of skin cancer because of its lethality [1, 5]. It has been estimated that 325,000 new cases of MM were diagnosed, and 57,000 people died from the disease worldwide in 2020, as well as more than 50% of cases of MM are predicted to occur in 2040 than in 2020 [1]. If MM is diagnosed and cured early, the five-year survival rate can be as high as 99% but drops to 65% or even 25% if the disease progresses to the lymph nodes or distant organs [6]. Therefore, it is crucial to realize early identification and stage assessment of MM. Clinical diagnostic techniques for MM include dermoscopy, reflective confocal microscopy (RCM), and excisional biopsy [6; 7; 8]. Dermoscopy has been proven to improve the diagnostic accuracy of MM [9; 10]. RCM, also known as confocal laser scanning microscopy, has demonstrated higher sensitivity and specificity than dermoscopy for the diagnosis of pigmented melanoma [11; 12]. However, the performance remains subject to lesion characteristics. The current gold standard for the diagnosis of MM is excisional biopsy and histopathological examination [7; 13]. However, such an approach relies heavily on subjective visual examination by the physician [5; 14]. The general visual indicators of MM include size, elevation, color, irregular borders, surface roughness, cellular morphology, etc. [15; 16]. Unfortunately, these features resemble benign skin lesions such as benign nevus (BE) [17; 18], making the diagnosis of melanoma difficult. It has been reported that the rate of misdiagnosis can be as high as 15%, influenced by subjective factors [19]. Furthermore, the histopathological examination is technically demanding due to the dependence on staining [20]. The staining process is based on a chemical reaction between the dye and the biological components, which needs strict restriction of the dye and operation, resulting in it being time-consuming [20; 21; 22]. Thus, it is necessary to develop an objective and rapid diagnostic technology for detecting MM from BE. Pathologically, it has been concluded that the collagen fibers in the extracellular matrix are tightly associated with disease progression [23; 24; 25; 26]. Therefore, an accurate characterization of these structures may be of great significance as a promising biomarker for distinguishing MM from BE. As a primary component of connective tissue, collagen fibers are organized linearly or helically by collagen supramolecular structures [26; 27]. The regular molecular structure or ordered units induce strong birefringence properties in collagen fibers [28; 29; 30; 31; 32]. This property can be measured by retardance-related parameters, such as scalar retardance [29; 30; 31; 32; 33; 34]. Changes in scalar retardance have been demonstrated to accompany alterations in collagen spatial structures in various severe pathologies, including vaginal prolapse [33], skin basal cell carcinoma [35], cervical neoplasia [36], glaucoma [37], etc. Numerous polarization-sensitive techniques have attracted much attention, due to their unique ability to measure polarized properties of light [38], especially the retardance induced by birefringent samples [29; 39; 40; 41; 42; 43; 44]. The most common methods for describing the retardance of polarized light are the intensity-based Mueller algebra and the field-based Jones algebra [23; 24; 25; 26; 27; 28; 29; 41; 42; 43; 45; 46; 47].