Cancer has been one of main causes of human deaths for many years. Early detection of cancer is essential to provide definitive treatment. Among many cancer treatment methods, nanoparticle-mediated photothermal therapy is considered as one of the promising cancer treatment methods because of its non-invasiveness and cancer-specific therapy. Ultrasound and photoacoustic imaging can be utilized for both cancer detection and photothermal therapy guidance. Ultrasound elasticity imaging can detect cancer using tissue elastic properties. Once cancer is diagnosed, spectroscopic photoacoustic imaging can be used to monitor nanoparticle delivery before photothermal therapy. When nanoparticles are well accumulated at the tumor, ultrasound and photoacoustic-based thermal imaging can be utilized for estimating temperature distribution during photothermal therapy to guide therapeutic procedure. In this dissertation, ultrasound beamforming, elasticity imaging, and spectroscopic photoacoustic imaging methods were developed to improve cancer detection and therapy guidance. Firstly, a display pixel based synthetic aperture focusing method was developed to fundamentally improve ultrasound image qualities. Secondly, an autocorrelation based sub-pixel displacement estimation method was developed to enhance signal-to-noise ratio of elasticity images. The developed elasticity imaging method was utilized to clinically evaluate the feasibility of using ultrasound elasticity imaging for prostate cancer detection. Lastly, a minimum mean square error based spectral separation method was developed to robustly utilize spectroscopic photoacoustic imaging. The developed spectroscopic photoacoustic imaging method was utilized to demonstrate ultrasound and photoacoustic image-guided photothermal cancer therapy using in-vivo tumor-bearing mouse models. The results of these studies suggest that ultrasound and photoacoustic imaging can assist both cancer detection and therapy guidance. / text