Abstract: A method for monitoring tissue response to cancer treatment by analyzing photoacoustic signals is provided. The method is capable of classifying different levels of tumor response for a tumor under treatment. Photoacoustic signals are obtained by scanning a tumor before and after treatment in given time intervals. Classification of the tumor response is achieved based on statistical features extracted from the photoacoustic signals. The similarities and dissimilarities between the statistical features are used to identify and classify the changes in tissue as the tumor responds to the treatment. To visualize the similarities and dissimilarities, a computed similarity metric is mapped to a multidimensional space, such as a two- or three-dimensional space. In this produced tissue response map, each point represents the tumor in a particular condition. Points that are farther apart in the tissue response map indicate more changes in tumor tissue due to changing condition and vise versa.

Abstract: A computing device system and method for detecting cell death in a biological sample is provided. A plurality of optical coherence tomography (OCT) data sets are received, each representative of OCT backscatter data collected from the biological sample and comprising respective signal fluctuation as a function of time at different respective times over a given time period. Respective indications of respective signal decorrelation rates are determined for each of the plurality of OCT data sets at each of the different respective time.