Since aggressive cancers are frequently hypermetabolic with angiogenic vessels, quantification of blood flow (BF) can be vital for cancer diagnosis. Our laboratory has developed a noncontact diffuse correlation tomography (ncDCT) system for 3-D imaging of BF distribution in deep tissues (up to centimeters). The ncDCT system employs two sets of optical lenses to project source and detector fibers respectively onto the tissue surface, and applies finite element framework to model light transportation in complex tissue geometries. This thesis reports our first step to adapt the ncDCT system for 3-D imaging of BF contrasts in human breast tumors. A commercial 3-D camera was used to obtain breast surface geometry which was then converted to a solid volume mesh. An ncDCT probe scanned over a region of interest on the breast mesh surface and the measured boundary data were used for 3-D image reconstruction of BF distribution. This technique was tested with computer simulations and in 28 patients with breast tumors. Results from computer simulations suggest that relatively high accuracy can be achieved when the entire tumor was within the sensitive region of diffuse light. Image reconstruction with a priori knowledge of the tumor volume and location can significantly improve the accuracy in recovery of tumor BF contrasts. In vivo ncDCT imaging results from the majority of breast tumors showed higher BF contrasts in the tumor regions compared to the surrounding tissues. Reconstructed tumor depths and dimensions matched ultrasound imaging results when the tumors were within the sensitive region of light propagation. The results demonstrate that ncDCT system has the potential to image BF distributions in soft and vulnerable tissues without distorting tissue hemodynamics. In addition to this primary study, detector fibers with different modes (i.e., single-mode, few-mode, multimode) for photon collection were experimentally explored to improve the signal-to-noise ratio of diffuse correlation spectroscopy flow-oximeter measurements.