1. A method for detecting and segmenting a lesion from longitudinal, time series, or multiparametric imaging by utilizing spectral embedding-based active contour (SEAC), the method comprising: (a) obtaining a plurality of images from a longitudinal, time series, or multi-parametric imaging; (b) applying spectral embedding (SE) to the longitudinal, time series, or multi-parametric imaging in a pixel-wise fashion to reduce a plurality of time point images to a single parametric embedding image (PrEIm), wherein the spectral embedding produces three smallest eigenvectors at each pixel location in the single parametric image by presenting color values in the parametric embedding image (PrEIm); (c) calculating spatial tensor-based gradients on the parametric embedding image (PrEIm) derived from spectral embedding (SE) eigenvectors; (d) selecting an initialization on the image; (e) evolving active contour (AC) on the parametric embedding image (PrEIm); and (f) detecting and segmenting the lesion based on morphological features derived from (e).