## 1 Introduction  
Cancer is one of the leading causes of mortality worldwide [1; 2; 3]. Bladder cancer has not only the highest recurrence rate amongst all cancer types, but also ranks as thirteenth in the context of mortality [4; 5]. Hence, early diagnostic and full resection of suspicious lesions need to be improved to minimize the likelihood of recurrence. Currently, the gold standard for bladder cancer detection is white light-guided cystoscopy (WLC) with transurethral resection of the bladder tumor (TURBT). The resected bladder biopsies are examined by histopathologists. As this method heavily depends on the subjective interpretation of the surgeon and the histopathologist, it is time-consuming and associated with high costs, therefore new strategies to overcome these limitations are of interest. Furthermore, the main disadvantage of conventional WLC is its lack of sensitivity to detect small lesions as stage Ta/T1 tumor or carcinoma in situ. Ta describes the stage of a tumor, which is superficial and does not invade the subepithelial connective tissue. T1 indicates the stage of tumor infiltrating the subepithelial connective tissue. T2 tumor invades the muscle and stage T3 tumor further penetrates perivesical tissue. T4 tumor reaches prostate stroma, seminal vesicles, uterus, vagina, pelvic wall or abdominal wall (TNM classification 2009). Several approaches, e.g., ultrasound, photodynamic diagnosis, narrow-band imaging, confocal laser endo-microscopy to improve diagnostics and potentially diagnose in vivo have been proposed [6; 7; 8]. Optical coherence tomography (OCT) is a label-free optical technique based on low coherence light interferometry allowing for fast cross-sectional views of tissue structure [9; 10; 11]. As this method is non-invasive, non-destructive and label-free it has found broad application in diagnostic of different types of skin cancer, oral cancer, lung cancer, breast cancer, colon cancer, prostate cancer and esophageal cancer [12]. [PERSON] et al. showed a combined OCT and ultrasound approach to investigate bladder cancer in a rat model [13]. In this study, diagnosis of bladder diseases were performed on inflammatory tissue and different stages of the tumor (Ta, T1, T2, T3 and T4). In previous studies, OCT has lacked discrimination of the different stages, due to limited imaging depth as further degenerated tumors infiltrated the muscle too deep. This limitation could be overcome by switching to longer interrogation wavelengths. Despite this drawback, OCT for human bladder cancer detection revealed clearly different structural features of healthy bladder tissue compared to carcinoma in situ and furthermore different stages of bladder cancer [14; 15]. As OCT imaging is limited to extract morphological features, no diagnosis of grading can be achieved. However, extraction of texture features in OCT images allows for automated analysis and is capable of discriminating healthy and pathologic tissue. First approaches to texture analysis were demonstrated on mouse lung tissue [16]. Furthermore, the feasibility of such an algorithm has been shown on the diagnosis of breast tissue [17]. As these algorithms look for textural features of OCT images, this approach can also be applied to OCT images acquired in the bladder discriminating different stages. Even though the lack to provide molecular information restricts OCT to the staging of bladder tissue via morphological features, grading still needs to be complemented by another modality. Raman spectroscopy (RS) is based on the inelastic light scattering between a photon and a molecule and the thereby excitation of molecular vibrations, providing molecular fingerprint information of the sample. The method has been widely used to successfully achieve discrimination between cancerous versus healthy tissue [18; 19; 20; 21; 22; 23; 24]. Complementary to OCT, RS provides high chemical sensitivity and can detect the smallest molecular changes between healthy and diseased tissue.