A multi-modality imaging system intended for clinical utilization has been developed. It is constructed around an existing fiber-bundle-based fluorescence confocal microendoscope. Additional imaging modalities have been implemented to expand the capabilities of the system and improve the accuracy of disease diagnosis. A multi-spectral mode of operation is one such modality. It acquires fluorescence images of a biological sample across a spectral range of sensitivity and explores the collected image data at any specified wavelength within that spectral range. Cellular structures can be differentiated according to their spectral properties. The relative distribution and concentration of the different cellular structures can potentially provide useful pathologic information about the imaged tissue. A spectral-domain optical coherence tomography (SDOCT) modality is another imaging technique integrated into the system. It provides a cross-sectional imaging perspective that is comparable to microscopic images obtained from histology slides and complementary to the en face view obtained from the confocal imaging modality. The imaging system uses a parallelized architecture (fiber-optic bundle, line of illumination) to increase the data acquisition speed. A one-dimensional scan is needed to capture 2D images in the confocal modality or a 3D data cube (two spatial dimensions and one spectral dimension) in the multi-spectral mode of operation. No scanning is required to capture a 2D OCT image. The fiber-bundle design is particularly critical for the SDOCT modality as it paves the way to novel fast endoscopic OCT imaging that has a high potential for translation into the clinic. The integrated multi-modality imaging system can readily switch between different imaging modalities, which will make it a powerful diagnostic tool in a clinical environment. It can provide valuable information about the morphology, the spectral and biochemical features, and the macroscopic architecture of tissue. It is believed that fast and accurate disease diagnosis can potentially be made based on all these characteristics.