Our study targets improved and accelerated diagnostics of bladder cancer with optical coherence tomography (OCT) and Raman spectroscopy (RS) ex vivo. OCT provides structural information on the penetration depth of the lesion, whereas RS complements this information with molecular characteristics regarding the likelihood of growth and spreading. Hence, the diagnostic findings include the determination of stage and grade of a tumor. The bladder specimens were scanned with OCT to detect suspicious lesions. Thereby, OCT was used as a red-flag technology to examine the bladder wall for abnormal tissue. Malignant bladder wall could be discriminated from healthy tissue. Upon identification of a cancerous lesion, RS added diagnostic information with molecular characteristics of the tumor regarding the grade. Texture analysis of OCT tomograms followed by k-nearest neighbour classification determined the stage of the lesion. Principal component analysis (PCA) of Raman spectra allowed for dimension reduction which was also fed into a knearest neighbour classifier allowing for classification of low-grade and high-grade tumors. We obtained an accuracy of 71% and 93% for staging and grading, respectively.